Used Car Price Prediction Dataset is a comprehensive collection of automotive information extracted from the popular automotive marketplace website, https://www.cars.com. This dataset comprises 4,009 data points, each representing a unique vehicle listing, and includes nine distinct features providing valuable insights into the world of automobiles.

• Brand & Model: Identify the brand or company name along with the specific model of each vehicle.
• Model Year: Discover the manufacturing year of the vehicles, crucial for assessing depreciation and technology advancements.
• Mileage: Obtain the mileage of each vehicle, a key indicator of wear and tear and potential maintenance requirements.
• Fuel Type: Learn about the type of fuel the vehicles run on, whether it's gasoline, diesel, electric, or hybrid.
• Engine Type: Understand the engine specifications, shedding light on performance and efficiency.
• Transmission: Determine the transmission type, whether automatic, manual, or another variant.
• Exterior & Interior Colors: Explore the aesthetic aspects of the vehicles, including exterior and interior color options.
• Accident History: Discover whether a vehicle has a prior history of accidents or damage, crucial for informed decision-making.
• Clean Title: Evaluate the availability of a clean title, which can impact the vehicle's resale value and legal status.
• Price: Access the listed prices for each vehicle, aiding in price comparison and budgeting.

This dataset is a valuable resource for automotive enthusiasts, buyers, and researchers interested in analyzing trends, making informed purchasing decisions or conducting studies related to the automotive industry and consumer preferences. Whether you are a data analyst, car buyer, or researcher, this dataset offers a wealth of information to explore and analyze.

🚗 Used Car Price Dataset: A dataset for predicting used car price 📊

Dive into the world of used cars with our dataset, perfect for predicting prices. It's a carefully selected set of data that car enthusiasts, analysts, and data scientists will find valuable. Whether you're curious or looking to analyze, this dataset is your guide to understanding the dynamics of how used cars are valued.

Key Features:

• 🛣️ Rich Attributes: Explore a number of attributes, including mileage, model year, fuel type, transmission, and more, providing a 360-degree view of each vehicle's specifications.
• 📉 Depreciation Insights: Uncover patterns in vehicle depreciation over time and across different makes and models, empowering you to make informed predictions about future price trends.
• 📱 Technological Integration: Seamlessly integrate our dataset into your predictive modeling pipelines, harnessing the power of technology to foresee changes in the used car market.

Potential Applications: - 📈 Market Research: Conduct in-depth market research to identify trends, fluctuations, and hotspots in the used car industry. - 🤖 Predictive Modeling: Build robust machine learning models to predict resale values, assisting buyers, sellers, and dealerships in making informed decisions. - 🚀 Business Strategy: Inform business strategies for used car dealerships, insurance companies, and financial institutions by understanding the underlying factors influencing pricing.

How to Use: 1. 🧑‍💻 Data Science Projects: Integrate this dataset into your data science projects to explore and analyze factors impacting used car prices. 2. 🚀 Predictive Modeling: Train machine learning models to predict resale values based on historical data and a wide array of vehicle attributes. 3. 🚗 Market Insights: Gain valuable insights into market dynamics, allowing you to stay ahead of trends and developments in the used car space.

Dataset Description:

1552 Rows, 15 Columns

Attributes:

1. car_name
2. registration_year
3. insurance_validity
4. fuel_type
5. seats
6. kms_driven
7. ownership
8. transmission
9. manufacturing_year
10. mileage(kmpl)
11. engine(cc)
12. max_power(bhp)
13. torque(Nm)
14. price(in lakhs)

Steps you can do:

1. Data Preprocessing 2. Data Visualization 3. Explarotary Data Analysis 4. Feature Selection and Transformation 5. Train-Test-Split 6. Model Creation (eg: Multiple Linear Regression) 7. Model Prediction

Give an upvote if it helps !!

This dataset contains the predicted prices of the asset Used Car over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Context This dataset contains information on used cars for sale, including model name, year of manufacturing, Km driven, price, and fuel type. The dataset can be used for a variety of applications such as price prediction, trend analysis, and market research. Content This data is scrape from https://www.carwale.com/ which is a popular platform in India for buying and selling cars. CarWale is a website and app that provides information about new and used cars in India. Users can research and compare different models, read reviews, and find dealerships in their area.

Used Cars Dataset

Overview This dataset contains information about used cars in the Indian market, comprising 15,000 entries with 11 detailed attributes. The data appears to be collected up to November 2024, providing a comprehensive view of the second-hand car market in India.

Dataset Features

Brand: Car manufacturer (e.g., Volkswagen, Maruti Suzuki, Honda, Tata)
Model: Specific car model (e.g., Taigun, Baleno, Polo, WRV)
Year: Manufacturing year of the vehicle (ranging from older models to 2024)
Age: Age of the vehicle in years
kmDriven: Total kilometers driven by the vehicle
Transmission: Type of transmission (Manual or Automatic)
Owner: Ownership status (first or second owner)
FuelType: Type of fuel (Petrol, Diesel, Hybrid/CNG)
PostedDate: When the car listing was posted
AdditionalInfo: Extra details about the vehicle
AskPrice: Listed price in Indian Rupees (₹)

Dataset Statistics

• Total entries: 14,993
• Columns: 11
• Memory usage: 1.94+ MB
• Data types: Mixed (int64 and object)

Potential Use Cases

• Price prediction modeling for used cars in India
• Market analysis of different car segments
• Study of depreciation patterns
• Analysis of fuel type preferences
• Understanding transmission preferences in the Indian market
• Examining the relationship between kilometers driven and pricing
• Brand value retention analysis

This dataset would be valuable for data scientists, automotive market analysts, and machine learning practitioners interested in the Indian automotive sector.

1) Data Introduction • The Extended Dataset for Used Car Prices Regression Dataset is a structured dataset designed to predict the collector’s value of used vehicles based on a variety of features related to car pricing. It includes key attributes such as model year, brand, model, vehicle type, fuel efficiency (MPG), and MSRP. The collection_car variable indicates whether a car is considered a collector’s item due to its rarity or historical significance.

2) Data Utilization (1) Characteristics of the Extended Dataset for Used Car Prices Regression Dataset: • The dataset contains key factors influencing vehicle value, such as miles_per_gallon, premium_version, and msrp (Manufacturer's Suggested Retail Price).

(2) Applications of the Extended Dataset for Used Car Prices Regression Dataset: • Collector car prediction model development: The dataset can be used to train machine learning classification models that predict whether a vehicle has collector value based on its characteristics. • Rare vehicle market analysis and targeted marketing: By identifying vehicles with high collector value, the dataset supports applications in used car marketing, insurance planning, and premium vehicle recommendation systems.

🚗 Used Car Price Prediction Dataset

📌 Subtitle

Comprehensive Used Car Dataset from India with 7,400 Listings and 29 Features for Price Prediction and Analysis

📝 Description

This dataset contains detailed information about used cars listed for sale in India.
It can be used for:

• Regression → Predicting car prices (sale_price)
• Classification → Predicting features like car_rating, car_availability, or warranty_avail
• EDA → Analyzing market trends, buyer preferences, and pricing strategies

The dataset is highly suitable for Machine Learning, Deep Learning, and Data Visualization projects.

📊 Columns Description

🔑 Key Points

• Rows: 7,400 used car listings
• Columns: 29 attributes (numerical, categorical, and boolean)
• Target Variable: sale_price
• Possible Tasks: Price Prediction, Trend Analysis, Buyer Behavior Modeling

💡 Inspiration

• Can we accurately predict the selling price of a used car?
• How do factors like fuel type, year of manufacture, and kilometers driven affect resale value?
• Do premium brands retain value better than budget cars?
• Can we identify market trends across cities in India?

Cleaned & Feature Engineered Car Price Dataset

Note:

This dataset does not belong to me. I originally got the dataset on Kaggle from 'taeefnajib'. I needed a dataset for a prediction model, so I cleaned this up, removed null values and added new columns. Do note that all the filled null values are not 100% accurate. This is why you can see some electric cars having V6 engines. However, a lot of empty horsepower columns have been cross-referenced from Wikipedia and brand websites and then filled.

Also, I did not encode columns. I did that so if someone chose to implement their own encoding methods, they would at least know what the column values actually mean.

Lastly, the dataset is basically ready to use with some minor preprocessing. Thanks again to 'taeefnajib' for providing me with the dataset.

Source

Original dataset: Used Car Price Prediction Dataset

Modifications

• Extracted horsepower, layout and engine capacity from the existing dataset
• filled all the null values, most of them are cross-referenced from reputable sources.
• Data is left in a verbose state so people can understand it when encoding

Files

• used_car_cleaned.csv: Final processed dataset ready for ML use, preferrable Regression

Columns

• brand — Manufacturer or company name of the car (e.g., Toyota, BMW).
• model_year — Year in which the car model was manufactured or launched.
• mileage — Total distance the car has travelled, in miles.
• fuel_type — Type of fuel used by the car (e.g., Petrol, Diesel, Electric).
• transmission — Gear system type of the car, such as Manual or Automatic.
• accident — Indicates whether the car has been in any reported accidents.
• clean_title — Shows if the car has a clean, non-salvage ownership title.
• price — The listed or market price of the car.
• horsepower — Engine power output, measured in HP (horsepower).
• engine_capacity — Volume of the engine, usually in litres (e.g., 2.0L).
• layout — Engine layout (i4,v6,v8).
• model — Specific model name of the car (e.g., Corolla, Civic, 3 Series).
• engine — Verbose engine name.

This dataset is designed for machine learning and data analysis projects focused on predicting the prices of cars based on various key attributes. It includes real-world data from multiple car listings, covering features such as brand, model, year, mileage, fuel type, transmission, and condition — all of which influence the final market price.

You can use this dataset to:

Build and evaluate regression models for car price estimation

Analyze which features most affect car value

Practice feature encoding, data preprocessing, and visualization

Compare performance between ML algorithms (Linear Regression, Random Forest, XGBoost, etc.)

Features

Column Name & Description

Car ID Unique identifier for each car listing

Brand Car manufacturer (e.g., Toyota, Honda, Suzuki)

Model Specific car model name

Year Manufacturing year of the car

Mileage Total distance driven (in kilometers)

Fuel Type Type of fuel used (Petrol, Diesel, Hybrid, Electric)

Transmission Type of gear system (Manual / Automatic)

Condition Overall car condition (New, Used, Excellent, etc.)

Price Market price of the car (target variable)

Snapshot img

US Used Car Market Size 2025-2029

The US used car market size is forecast to increase by USD 40.2 billion, at a CAGR of 4.3% between 2024 and 2029.

The used car market in the US is witnessing significant growth, driven by the excellent value proposition that used cars offer to consumers. The increasing popularity of websites dedicated to selling used cars has expanded market reach and convenience, allowing consumers to browse and purchase vehicles online. Stringent emission regulations are restricting the sales of non-compliant used cars, necessitating investments in upgrading and maintaining commercial vehicle fleets to meet regulatory requirements. These regulations necessitate investments in emission testing and certification processes, increasing operational costs for dealers. To capitalize on opportunities, dealers can focus on offering certified pre-owned vehicles and implementing robust emission testing procedures.
Additionally, leveraging digital marketing strategies and offering flexible financing options can help attract and retain customers. Overall, the used car market presents both challenges and opportunities for players, requiring strategic planning and innovation to succeed.

What will be the size of the US Used Car Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The used car market in the US continues to evolve, with various sectors adapting to emerging trends and technologies. Vehicle data analysis plays a pivotal role in understanding vehicle depreciation curves and return on investment for dealers. Payment processing systems streamline sales transactions, while sales performance metrics and customer lifetime value inform strategic decision-making. Fraud detection systems ensure compliance with legal standards, and insurance cost factors influence acquisition channel efficiency. Inventory turnover rate, a key performance indicator, varies across dealerships. Compliance audits and dealer training programs maintain legal compliance and improve customer satisfaction. Market penetration rate and resale value prediction help dealers optimize pricing models.
Consumer protection laws and financing product offerings shape customer trust and loyalty. Operating costs analysis, customer service feedback, and sales conversion rates contribute to profit margin calculation. Risk assessment models, employee performance metrics, marketing spend efficiency, and pricing model validation are essential for long-term success. A recent study reveals a 5% increase in sales for dealerships implementing advanced data analytics. Industry growth is expected to reach 3% annually, driven by these evolving market dynamics.

How is this market segmented?

The US used car market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Distribution Channel

  3P channel sales
  OEM channel sales


Product

  Mid size
  Full size
  Compact size


Vendor Type

  Organized
  Unorganized


Fuel Type

  Diesel
  Petrol


Geography

  North America

    US

By Distribution Channel Insights

The 3P channel sales segment is estimated to witness significant growth during the forecast period.

The used car market in the US is an active and dynamic sector, driven by various factors. With the constant launch of new vehicle models, the supply of used cars increases, resulting in lower prices compared to new cars. This trend encourages car owners to sell their vehicles and upgrade to newer models, shortening the average ownership cycle. Online advertising platforms play a significant role in connecting buyers and sellers. Pre-purchase inspections and vehicle history reports ensure transparency and build trust. Repairs cost estimation and parts sourcing networks help in managing the expenses of used car ownership. Market segmentation strategies cater to different customer needs, while customer relationship management tools foster loyalty.

Emissions testing standards ensure the environmental sustainability of used vehicles. Auto appraisal value tools help in determining fair prices, and loan term comparison aids in financing decisions. Marketing campaign effectiveness is measured through customer acquisition cost and interest rate calculation. Mobile apps offer functionalities like mechanical inspection checklists, paint depth measurement, and damage assessment tools. Dealer inventory management, detailing services, and vehicle photography techniques enhance the sales process. Industry growth is expected to continue, with the used car market projected to expand by 3% annually. For instance, a dealership successfully increased its sales by 15% thr

The German used car market is predicted to grow at a compound annual growth rate of **** percent between 2021 and 2027. By 2027, the market is expected to have grown to ****** billion US dollars, an increase of ***** billion US dollars from its size in 2021.

Snapshot img

Used Car Market Size 2025-2029

The used car market size is valued to increase by USD 885.3 billion, at a CAGR of 7.4% from 2024 to 2029. Increasing number of new models of cars launched due to high competition will drive the used car market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 41% growth during the forecast period.
By Vehicle Type - Compact segment was valued at USD 856.10 billion in 2023
By Channel - Organized segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 67.95 billion
Market Future Opportunities: USD 885.30 billion
CAGR from 2024 to 2029 : 7.4%

Market Summary

The market, a significant and dynamic sector of the global automotive industry, experienced a record-breaking year in 2021. According to the International Organization of Motor Vehicle Manufacturers, approximately 35 million used cars were sold worldwide, marking a 5% increase compared to the previous year. This growth can be attributed to several key drivers. First, the increasing number of new models launching due to heightened competition has led to a larger supply of used cars. Moreover, the growing demand for car subscription services and car-sharing platforms has created new opportunities for consumers to access affordable, flexible transportation solutions. The market's evolution has been shaped by various trends and challenges.
Technological advancements, such as the integration of electric and autonomous vehicle technologies, have transformed the market landscape. Additionally, changing consumer preferences, including a focus on sustainability and cost savings, have influenced market dynamics. Looking ahead, the market is expected to continue its growth trajectory. As the global population becomes increasingly urbanized and transportation needs become more diverse, the demand for used cars is likely to increase. Furthermore, the ongoing digitalization of the automotive industry will create new opportunities for innovation and disruption. In conclusion, the market is a vital and evolving sector that offers significant opportunities for businesses.
Its growth is driven by factors such as increased competition, the rise of car subscription services, and changing consumer preferences. As the market continues to adapt to technological advancements and shifting trends, it will remain a dynamic and exciting space for innovation and growth.

What will be the Size of the Used Car Market during the forecast period?

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How is the Used Car Market Segmented ?

The used car industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Vehicle Type

  Compact
  SUV
  Mid size


Channel

  Organized
  Unorganized


Fuel Type

  Diesel
  Petrol


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Vehicle Type Insights

The compact segment is estimated to witness significant growth during the forecast period.

The market continues to evolve, with the compact segment experiencing significant growth in APAC and Europe. This class of vehicles, positioned between subcompact and mid-size cars, gains popularity due to increasing consumer demand for personal mobility and more efficient, eco-friendly options. In densely populated regions, compact cars offer easier handling and lower emissions, contributing to a 50% market share in some regions. Popular pre-owned models like the Fiat Panda and Volkswagen Golf in Europe undergo rigorous pre-sale inspections, including body damage assessment, suspension component inspection, and mileage verification methods. Refurbishment techniques, such as automotive diagnostic tools and mechanical inspection procedures, ensure optimal engine performance and safety.

Consumer review aggregation and title verification services provide transparency, while repair cost estimation and parts replacement costs inform potential buyers. Fuel efficiency ratings, detailing services, and pre-purchase inspection checklists further enhance the buying experience. Online vehicle marketplaces employ pricing algorithms, vehicle financing options, and auction platform data to facilitate sales. Electrical system testing, maintenance record analysis, and emissions testing standards ensure transparency and safety. Safety recall checks, brake system evaluation, and fluid level checks complete the comprehensive assessment process.

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The Compact segment was valued at USD 856.10 billion in 2019 and showed a gradual increase dur

The used car market is projected to reach over *** trillion U.S. dollars in 2027, up from *** trillion in 2020. This represents a compound annual growth rate of around *** percent across seven years. This growth is in part attributed to a shift in car ownership patterns across the globe, as well as the rise of online sales channels, which make used cars more accessible to customers.

This dataset is part of the KaggleX Skill Assessment Challenge focused on predicting the prices of used cars. The dataset contains various attributes of used cars, including make, model, year, mileage, and other relevant features that can help in predicting the car's price. The goal is to build a predictive model that can accurately estimate the market value of used vehicles based on these features

Dataset Features:

1. Make: The manufacturer of the car (e.g., Toyota, Ford, BMW).
2. Model: The specific model of the car (e.g., Corolla, Mustang, X5).
3. Year: The year the car was manufactured.
4. Mileage: The total miles driven by the car.
5. Engine: Details about the engine (e.g., 2.0L, V6).
6. Fuel Type: The type of fuel the car uses (e.g., Petrol, Diesel, Electric).
7. Transmission: The type of transmission (e.g., Manual, Automatic).
8. Price: The price of the car (target variable for prediction).

Usage:

This dataset is intended for participants to train machine learning models to predict car prices. It can be used to explore different algorithms, feature engineering techniques, and model evaluation methods. The ultimate goal is to achieve the highest accuracy in predicting the price of used cars in the test set

Files: - - train.csv: Training data with features and the target price. - test.csv: Test data with features (excluding the target price). - sample_submission.csv: A sample submission file in the correct format for Kaggle submissions.

Participants are encouraged to preprocess the data, explore various machine learning models, and fine-tune their approaches to enhance prediction accuracy. Sharing insights and approaches in Kaggle notebooks is also highly encouraged to foster learning and collaboration within the community.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Used Cars and Trucks in U.S. City Average (CUSR0000SETA02) from Jan 1953 to Sep 2025 about used, trucks, vehicles, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

Used Car Prices YoY in the United States decreased to 0 percent in October from 2 percent in September of 2025. This dataset includes a chart with historical data for the United States Used Car Prices YoY.

In 2021, the used car market in the United Kingdom was worth around ****** billion U.S. dollars. This market size is expected to reach close to ***** billion U.S. dollars by 2027, with a compound annual growth rate of **** percent between 2022 and 2027. Used vehicles were the main passenger car segment in the country in 2021, representing some **** million sales.

Used Car Prices MoM in the United States decreased to -2 percent in October from -0.20 percent in September of 2025. This dataset includes a chart with historical data for the United States Used Car Prices MoM.

View monthly updates and historical trends for US Consumer Price Index: Used Cars and Trucks. Source: Bureau of Labor Statistics. Track economic data with…

The global used car market, valued at approximately $XX million in 2025 (assuming a logical estimation based on the provided CAGR of 10% and a known market size at an earlier point in time – this would require additional data to give a precise figure), is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 10% from 2025 to 2033. This expansion is fueled by several key factors. Increasing vehicle ownership, particularly in developing economies, coupled with the rising preference for more affordable transportation options, significantly boosts demand. Technological advancements, including online marketplaces and improved vehicle inspection services, streamline the buying and selling processes, further accelerating market growth. The shift towards subscription-based car ownership models and the growing acceptance of used vehicles as a viable alternative to new cars also contribute to the market's dynamism. Different vehicle types within the market exhibit varying growth trajectories, with SUVs and MPVs often leading in sales due to their versatility and family-friendly features. The organized sector, encompassing established dealerships and online platforms, is steadily gaining market share from the unorganized sector due to increased transparency, better financing options, and enhanced customer trust. Geographical variations in market performance are evident. North America and Europe currently dominate the market, with mature economies and strong established automotive infrastructures. However, rapid economic growth and rising disposable incomes in Asia-Pacific regions, particularly in India and China, are propelling significant market expansion in these areas, presenting lucrative opportunities for both established and emerging players. Challenges remain, including fluctuations in used car prices influenced by macroeconomic factors, concerns about vehicle reliability, and the growing environmental consciousness driving demand for more fuel-efficient options. Nevertheless, the long-term outlook for the used car market remains positive, with continued expansion anticipated throughout the forecast period. The competitive landscape is fiercely contested, with established global players like Hertz, Cox Automotive, and CarMax competing alongside regional players and emerging online platforms. Strategic acquisitions, technological investments, and expanding service offerings are key strategies employed by companies to gain a competitive edge and cater to evolving consumer preferences. This comprehensive report provides a detailed analysis of the global used car industry, covering the period from 2019 to 2033. With a base year of 2025 and an estimated year of 2025, the report forecasts market trends and growth opportunities within the multi-billion dollar sector. The study incorporates historical data (2019-2024), analyzes current market dynamics (2025), and projects future growth (2025-2033). This report is invaluable for industry stakeholders, investors, and anyone seeking to understand the complexities and potential of this dynamic market. Keywords: used car market, used car sales, used car prices, used car industry trends, pre-owned car market, second-hand car market, automotive market analysis, used car valuation, online used car market. Recent developments include: March 2022: TrueCar Inc. launched a new online car-buying marketplace called TrueCar+. TrueCar+ will provide consumers with a more flexible and personalized car buying experience for new and used vehicles., January 2022: General Motors launched Carvago to capitalize on the inflated used car. CarBravo will draw from General Motors' pool of available used cars, along with those of its franchised dealerships., September 2021: Mobil88 launched the Mo88i application to make buying and selling used cars easier. Mo88i is a platform for buying and selling used cars that are trusted, easy, fast, and efficient. This includes car inspections and estimated bid prices. It also ends with financing and vehicle insurance submissions., March 2021: Penske Automotive Group Inc. announced that it adopted CarShop as its global brand for its used vehicle SuperCenters. The company renamed its six used vehicles SuperCenters in the United States from CarSense to CarShop.. Key drivers for this market are: Increasing Demand For Electric School Buses. Potential restraints include: Uncertainty of The Global Pandemic. Notable trends are: Strengthening of Online Infrastructure Positively Affecting the Used Cars Market.