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Vehicle Price Prediction Dataset
Data Science and Analytics
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Free
About
Web-scrapped from car resale websites, this data includes numerous details about used cars, such as their make, model, year, and mileage, along with their respective selling prices. This data is particularly useful for analysing the used car market, building price prediction models, and understanding the factors that influence vehicle resale values.
Columns
- Car_Name: The full name of the car as displayed in the advertisement.
- Make: The manufacturer of the car.
- Model: The specific model of the car.
- Make Year: The year the car was manufactured.
- Color: The exterior colour of the car.
- Body Type: The style of the car's body.
- Mileage Run: The total kilometres the car has been driven.
- No of Owners: The number of previous owners.
- Seating Capacity: The total number of seats in the car.
- Fuel Type: The type of fuel the car uses.
- Fuel Tank Capacity(L): The capacity of the fuel tank in litres.
- Engine Type: The model and type of the car's engine.
- CC Displacement: The cubic capacity of the engine.
- Transmission: The kind of transmission.
- Transmission Type: The type of transmission.
- Power(BHP): The maximum power of the engine in Brake Horsepower.
- Torque(Nm): The maximum torque of the engine in Newton-metres.
- Mileage(kmpl): The average fuel efficiency in kilometres per litre.
- Emission: The emission standard the car complies with.
- Price: The selling price of the car.
Distribution
The dataset is available in CSV format (FINAL_SPINNY_900.csv) with a size of 167.79 kB. It contains 976 records and 20 columns. All columns are 100% valid with no missing values.
Usage
Ideal applications for this dataset include:
- Developing regression models to predict used car prices.
- Performing market analysis on the second-hand car industry.
- Training machine learning algorithms for feature importance analysis.
- Data visualisation projects to explore trends in used car sales.
Coverage
The dataset contains information on cars manufactured between 2011 and 2022. While specific geographic or demographic data is not provided, the car makes and models are common in various markets. The data primarily consists of petrol (80%) and diesel (20%) vehicles, with hatchbacks being the most common body type (50%). Most vehicles listed have had only one previous owner (84%).
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For building predictive models and conducting market research on vehicle valuation.
- Machine Learning Engineers: To train, test, and validate regression and linear regression algorithms.
- Automotive Industry Professionals: To gain insights into resale market trends, pricing strategies, and popular models.
- Students and Researchers: For academic projects related to data science, transportation, and economics.
Dataset Name Suggestions
- Used Car Resale Market Data
- Vehicle Price Prediction Dataset
- Used Automobile Listings
- Automobile Resale Value Analysis
Attributes
Original Data Source: Vehicle Price Prediction Dataset
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