Dark Mode
Vehicle Depreciation Analysis Dataset
Stock & Market Data
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Dive into the world of used cars with this dataset, ideal for predicting prices. It is a carefully selected set of data that car enthusiasts, analysts, and data scientists will find valuable. Whether you are curious or looking to analyse, this dataset is your guide to understanding the dynamics of how used cars are valued. It features a number of attributes, including mileage, model year, fuel type, transmission, and more, providing a 360-degree view of each vehicle's specifications. You can uncover patterns in vehicle depreciation over time and across different makes and models, empowering you to make informed predictions about future price trends. This dataset integrates seamlessly into predictive modelling pipelines, harnessing the power of technology to foresee changes in the used car market.
Columns
- car_name: The name of the car.
- registration_year: The vehicle's registration year.
- insurance_validity: The type of insurance associated with the vehicle.
- fuel_type: The type of fuel the car uses.
- seats: The number of seats available in the car.
- kms_driven: The total kilometres the car has been driven.
- ownership: The number of previous owners the car has had.
- transmission: The car's transmission mode (e.g., Manual, Automatic).
- manufacturing_year: The year the car was manufactured.
- mileage(kmpl): The car's mileage in kilometres per litre.
- engine(cc): The engine capacity in cubic centimetres.
- max_power(bhp): The maximum power output in brake horsepower.
- torque(Nm): The torque in Newton metres.
- price(in lakhs): The price of the used car, denominated in lakhs.
Distribution
The dataset contains 1552 rows and 15 columns, with a file size of 193.82 kB. The data is typically provided in a CSV format.
Usage
- Market Research: Conduct in-depth market research to identify trends, fluctuations, and hotspots in the used car industry.
- Predictive Modelling: Build robust machine learning models to predict resale values, assisting buyers, sellers, and dealerships in making informed decisions. Train machine learning models to predict resale values based on historical data and a wide array of vehicle attributes.
- Business Strategy: Inform business strategies for used car dealerships, insurance companies, and financial institutions by understanding the underlying factors influencing pricing.
- Data Science Projects: Integrate this dataset into data science projects to explore and analyse factors impacting used car prices.
- Market Insights: Gain valuable insights into market dynamics, allowing users to stay ahead of trends and developments in the used car space.
Coverage
The dataset's temporal scope is indicated by the 'registration_year' and 'manufacturing_year' columns, with common entries including years such as 2017 and 2018. The exact geographic and demographic scope is not explicitly detailed within the provided source material.
License
CC0: Public Domain
Who Can Use It
- Car Enthusiasts: For gaining a deeper understanding of vehicle valuation.
- Analysts and Data Scientists: For in-depth analysis, exploring factors impacting prices, and integrating into data science projects.
- Buyers and Sellers: To make informed decisions regarding used car values.
- Dealerships: To inform business strategies and predict resale values.
- Insurance Companies: To understand pricing factors for business strategy.
- Financial Institutions: To inform financial strategies related to vehicle valuation.
Dataset Name Suggestions
- Used Car Price Prediction Dataset
- Automobile Resale Value Data
- Vehicle Depreciation Analysis Dataset
- Car Market Trends Data
- Second-hand Car Pricing Data
Attributes
Original Data Source: Vehicle Depreciation Analysis Dataset
QUALITY