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.

Gain valuable insights into the automotive market with our comprehensive Car Prices Dataset. Designed for businesses, analysts, and researchers, this dataset provides real-time and historical car pricing data to support market analysis, pricing strategies, and trend forecasting.

Dataset Features

Vehicle Listings: Access detailed car listings, including make, model, year, trim, and specifications. Ideal for tracking market trends and pricing fluctuations. Pricing Data: Get real-time and historical car prices from multiple sources, including dealerships, marketplaces, and private sellers. Market Trends & Valuations: Analyze price changes over time, compare vehicle depreciation rates, and identify emerging pricing trends. Dealer & Seller Information: Extract seller details, including dealership names, locations, and contact information for lead generation and competitive analysis.

Customizable Subsets for Specific Needs Our Car Prices Dataset is fully customizable, allowing you to filter data based on vehicle type, location, price range, and other key attributes. Whether you need a broad dataset for market research or a focused subset for competitive analysis, we tailor the dataset to your needs.

Popular Use Cases

Market Analysis & Pricing Strategy: Track vehicle price trends, compare competitor pricing, and optimize pricing strategies for dealerships and resellers. Automotive Valuation & Depreciation Studies: Analyze historical pricing data to assess vehicle depreciation rates and predict future values. Competitive Intelligence: Monitor competitor pricing, dealership inventory, and promotional offers to stay ahead in the market. Lead Generation & Sales Optimization: Identify potential buyers and sellers, track demand for specific vehicle models, and enhance sales strategies. AI & Predictive Analytics: Leverage structured car pricing data for AI-driven forecasting, automated pricing models, and trend prediction.

Whether you're tracking car prices, analyzing market trends, or optimizing sales strategies, our Car Prices Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

Context :

In order to assist data scientists, analysts, and machine learning enthusiasts in creating predicting models for automobile pricing, the automobile Price Prediction Dataset is intended to offer an extensive collection of vehicle-related information. In order to replicate a genuine automobile market, the dataset includes a wide variety of car brands, models, manufacture years, and technical characteristics. It can be used to investigate how different elements affect an automobile's resale value, including mileage, engine size, fuel type, gearbox type, and brand reputation. Projects concentrating on price optimization, data visualization, and regression analysis in the automotive sector will benefit greatly from this dataset.

Content :

Ten attributes and 2,500 entries make up this dataset, each of which represents a crucial aspect of a distinct car. Vehicle ID, Brand, Model, Year of production, Engine Capacity (liters), Fuel Type, Transmission Type (manual or automatic), Mileage (kilometers), Condition (new, used, or like new), and Price (in USD) are among the factors. Effective analysis and modeling are made possible by the completeness and organization of all the values. Regression models for predicting automobile values, spotting market trends, and investigating connections between vehicle features and their effect on valuation can all be successfully trained using this dataset.

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.

🚗 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

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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 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…

In 2024, the average selling price of used vehicles came to around ****** U.S. dollars. In 2024, new automobiles and light trucks were on average almost ****** U.S. dollars more expensive than used light vehicles. The used car boom As the price for new vehicles has been increasing, more Americans are turning towards buying second-hand cars and light trucks. Buying new cars and light trucks is typically seen as a privilege that few may do often. Generally, used vehicle sales are on the rise in most countries. Thanks to ever-improving technology, automobiles may keep running for many years and remain in good condition. This allows the average age of light vehicles in operation in the United States to increase slowly. Although new cars are often seen as status symbols, vintage cars are also very popular in the United States, the main reason for this trend being aesthetic and cultural values.

🚗 2025 Used Car Market Dataset 🚗 This dataset is carefully prepared for data scientists, analysts, and researchers who want to analyze the 2025 used car market. With approximately 2,500 rows and 13 different features, this dataset serves as a powerful resource for exploring pricing trends, brand-model preferences, and vehicle history.

📊 Dataset Contents:

price → Vehicle price brand → Brand model → Model year → Manufacturing year mileage → Mileage information title_status → Vehicle title status (Clean, Salvage, etc.) color → Color information vin, lot → Vehicle identification details 🎯 Use Cases: ✔️ Machine learning projects – Price prediction, regression models ✔️ Data analysis & visualization – Analyzing market trends ✔️ Used car market research

🔹 This dataset is clean, well-structured, and ready for use—start your analysis right away! We’d love to hear feedback from the Kaggle community. 🚀

👉 Let’s explore this data and uncover valuable insights together! 💡

The European used car market continues to experience elevated prices, with the Harmonized Consumer Price Index for used cars in the Euro area reaching 121.24 in February 2025. This represents a significant increase of 21.24 points compared to the base year. The upward trend in used car prices began in early 2021 and has yet to show substantial signs of returning to pre-pandemic levels. Despite this persistent elevation, there is a growing sentiment among industry professionals that prices may start to stabilize or even decrease in the near future. Dealer expectations and market dynamics A December 2024 survey revealed that over 40 percent of European used car dealers anticipated a decrease in used car prices for 2025. This expectation aligns with the recent flattening of the price index curve observed in late 2024 and early 2025. However, about a third of the surveyed dealers believed prices would remain stable, indicating a divided outlook on the market's future direction. Consumer behavior and regional variations The used car market continues to play a significant role in vehicle ownership, particularly among younger Europeans. Nearly 60 percent of household cars available to people under 30 years old in Europe were purchased as used vehicles. This trend varies across countries, with France and Norway showing higher rates of used car ownership among young people compared to Southern European countries like Spain and Italy. Additionally, regional differences in used car mileage and transaction volumes highlight the diverse nature of the European used car market. Spain, for instance, reported the highest year-over-year increase in used car transactions as of the fourth quarter of 2024, with a 12.3 percent rise.

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.

Graph and download economic data for Consumer Price Index for All Urban Consumers: New Vehicles in U.S. City Average (CUUR0000SETA01) from Mar 1947 to Sep 2025 about vehicles, urban, new, consumer, CPI, inflation, price index, indexes, price, and USA.

United States - Consumer Price Index for All Urban Consumers: Used Cars and Trucks in U.S. City Average was 184.56800 Index 1982-84=100 in September of 2025, according to the United States Federal Reserve. Historically, United States - Consumer Price Index for All Urban Consumers: Used Cars and Trucks in U.S. City Average reached a record high of 216.87600 in February of 2022 and a record low of 20.00000 in March of 1956. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Consumer Price Index for All Urban Consumers: Used Cars and Trucks in U.S. City Average - last updated from the United States Federal Reserve on December of 2025.

1) Data Introduction • The Used Car Prices in india dataset contains information on the prices and related characteristics of used cars sold in India. • Key features include the car’s brand, model, manufacturing year, mileage, fuel type, transmission type, number of owners, engine displacement, horsepower, number of seats, and new car price.

2) Data Utilization (1) Characteristics of the Used Car Prices in india Dataset • This dataset includes various attributes related to the prices of used cars traded in India, making it useful for analyzing trends in the used car market. • It provides valuable data for analyzing and predicting the factors that affect used car prices.

(2) Applications of the Used Car Prices in india Dataset • Market Analysis: This dataset is useful for analyzing trends in the used car market, understanding price fluctuations, and identifying patterns in market demand. • Predictive Modeling: Based on the various attributes, predictive models can be developed to estimate the prices of used cars. • Business Insights: This data can be leveraged to analyze consumer preferences, market demand, and pricing strategies, helping businesses formulate their market strategies.

In the United States, the average selling price for a new light vehicle came to around ****** U.S. dollars in 2024. New light vehicles were about *** percent more expensive in 2024 than in 2023. What is the price of a new car in the U.S.?     New automobiles and light trucks were on around ****** U.S. dollars more expensive than used light vehicles: the average selling price for used vehicles amounted to about ****** U.S. dollars in 2024. This increasing price gap between new and used vehicles is partly linked to the industry's recovery from the semiconductor shortage, which led to higher new vehicle inventory and reduced pressure on the used vehicle market. The semiconductor shortage  The hike in prices across the board recorded in 2022 can be in part attributed to the global automotive chip shortage, which started in 2021 as demand rebounded from the COVID-19 pandemic. The average price rise could be observed across segments, with new full-size SUV/crossover vehicles averaging ****** U.S. dollars as of December 2022.

United States - Producer Price Index by Industry: New Car Dealers: Vehicle Sales was 79.03600 Index Dec 1999=100 in August of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: New Car Dealers: Vehicle Sales reached a record high of 201.85900 in June of 2022 and a record low of 61.20000 in April of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: New Car Dealers: Vehicle Sales - last updated from the United States Federal Reserve on December of 2025.

This dataset provides comprehensive details on used car listings, including vehicle specifications, features, pricing, and more. It's valuable for analyzing car prices, trends, and customer preferences in the automotive market.

Columns Description

• make_model: The brand and model of the vehicle (e.g., 'Audi A1').
• body_type: The body style of the vehicle, such as Sedan, Compact, or Station Wagon.
• price: The listed price of the car in currency.
• vat: Indicates the VAT status for the vehicle's price (e.g., VAT deductible, Price negotiable).
• km: The total mileage (in kilometers) of the vehicle, indicating its usage.
• Type: Condition of the vehicle, whether it's 'Used' or 'New'.
• Fuel: Type of fuel the vehicle uses, such as 'Diesel', 'Benzine', etc.
• Gears: The number of gears in the vehicle's transmission.
• Comfort_Convenience: Comfort and convenience features, such as 'Air conditioning', 'Leather steering wheel', 'Cruise control', and more.
• Entertainment_Media: Media features available in the vehicle, including 'Bluetooth', 'MP3', 'Radio', etc.
• Extras: Additional features like 'Alloy wheels', 'Sport suspension', etc.
• Safety_Security: Safety features like 'ABS', 'Airbags', 'Electronic stability control', 'Isofix', etc.
• age: Age of the car (calculated based on the model year).
• Previous_Owners: The number of previous owners the car has had.
• hp_kW: Engine power in kilowatts (kW), indicating the performance capacity of the engine.
• Inspection_new: Indicates whether the car has recently undergone an inspection (1 for yes, 0 for no).
• Paint_Type: The type of paint on the car, such as 'Metallic', 'Matte', etc.
• Upholstery_type: The material used for the interior upholstery, such as 'Cloth', 'Leather', etc.
• Gearing_Type: The type of transmission the car uses, either 'Automatic' or 'Manual'.
• Displacement_cc: The engine displacement in cubic centimeters (cc), indicating the size of the engine.
• Weight_kg: The total weight of the vehicle in kilograms.
• Drive_chain: The type of drivetrain, indicating whether it's 'Front' or 'Rear' wheel drive.
• cons_comb: The combined fuel consumption in liters per 100 kilometers.

Key Features

• Vehicle Specifications: Covers details like make, model, body type, fuel type, and more.
• Comfort & Safety Features: Includes information on air conditioning, safety features, and other convenience options.
• Performance Metrics: Provides data on mileage, engine power, weight, and fuel consumption.
• Pricing Information: Insights into vehicle pricing, VAT status, and other cost-related details.

Ideal Use Cases

• Price Prediction: Model car prices based on features like mileage, fuel type, and performance.
• Market Analysis: Explore trends and preferences in the used car market, by type, region, or other metrics.
• Customer Segmentation: Segment the dataset to analyze different customer preferences for car types, features, or price ranges.
• Feature Importance: Identify the most important factors influencing car prices (e.g., fuel type, mileage, age).

This dataset is ideal for machine learning, data analysis, and business intelligence applications in the automotive industry.

Inventory Search API - Search inventories to access detailed vehicle breakdowns, including photos, prices, locations and installed equipment. - $0.2 per 100 calls

VIN History API - Enter a 17 digit VIN to see the price history, changing odometer readings & full details about each car for up to six years back. - $0.6 per 100 calls

Dealer API - Check inventories by unique dealer ID or locate and view inventories for multiple dealerships in geographical areas. - $0.25 per 100 calls

Enhanced Vin Decoder - Submit a 17 digit VIN to pull back year, make, model and trim with the installed equipment and detailed vehicle specs. - $8.0 per 100 calls

CRM Cleanse API - Use our data to clean prospect lists. Track any car's appearance online by 17 digit VIN and know when it has been sold. - $0.8 per 100 calls

Cars Market APIs - Get Market Days Supply value for a car - $0.6 per 100 calls

Private Party Inventory Search API - Search private seller listings by any combination of layered criteria across the US and Canada. - $1.0 per 100 calls

Auction Inventory Search API - Search auction listings by any combination of layered criteria across the US and Canada. - $0.8 per 100 calls

Dealer Recent Inventory Search API - Search by any combination of criteria to view any dealership's inventory from the last 90 days across the US and Canada. - $0.6 per 100 calls

Dealer Active Inventory Search API - Fetch dealers active inventory - $20.0 per 100 calls

Inventory Ranking API - Perform ranked search with dynamic rank criteria - $0.8 per 100 calls

OEM Incentive Search API - Search Incentive Programs for 30+ car manufacturer at one place - $0.6 per 100 calls

Cached Images API - Get a cached version of the car images of the photos listed on the VDP on the dealer's website. - $0.1 per 100 calls

Recall Lookup By VIN - Get open recall information for a VIN from multiple OEM microsites - $0.3 per 100 calls

------ Heavy Equipment APIs ------ Inventory Search API - Search used heavy equipment listings by layered criteria to get prices, options, photos, videos and equipment details. - $0.2 per 100 calls

Dealer API - Search individual dealerships or groups of dealers to see their inventories and dealer profiles. - $0.25 per 100 calls

------ Motorcycles APIs ------ Inventory Search API - Search motorcycle listings by layered criteria to get prices, options, photos, videos and equipment details. - $0.2 per 100 calls

Dealer API - Search individual dealerships or groups of dealers to see their inventories and dealer profiles. - $0.25 per 100 calls

------ Recreational Vehicles APIs ------ Inventory Search API - Search recreational vehicle listings by layered criteria to get prices, options, photos, videos and equipment details. - $0.2 per 100 calls

Dealer API - Search individual dealerships or groups of dealers to see their inventories and dealer profiles. - $0.25 per 100 calls

1. Understanding the Features

Brand and Model: Analyze how different brands and models influence car prices. Are luxury brands significantly more expensive than economy brands? Year of Manufacture: Discuss the depreciation of car prices over time. How does the year affect pricing, and are there notable trends for specific brands? Engine Size: Explore the relationship between engine size and price. Does a larger engine correlate with a higher price, and how does this vary across different fuel types? Fuel Type: Evaluate how fuel types (Petrol, Diesel, Electric, Hybrid) impact pricing. Are electric vehicles priced higher due to their technology, or do they vary based on other factors? Transmission: Discuss if manual or automatic transmissions affect car pricing, especially in different markets or demographics.

2. Price Predictions and Modeling

Machine Learning Models: Explore which models (e.g., linear regression, decision trees, or ensemble methods) are best suited for predicting car prices using this dataset. Feature Importance: Discuss the importance of different features in predicting price. Which features contribute most to the price prediction accuracy, and how can feature selection improve the model?

3. Market Trends and Insights

Price Distribution: Analyze the distribution of car prices. Are there a lot of high-priced luxury cars, or is the dataset skewed towards more affordable options? Mileage vs. Price: Investigate the correlation between mileage and price. How does higher mileage affect pricing, and is there a threshold where price reduction becomes significant? Condition Impact: Discuss how the condition of the car (New, Used, Like New) influences the price. Are there significant price drops for used cars compared to new ones?

4. Regional Analysis

Location Impact: If geographic location is included, discuss how prices vary by region. Are there markets where certain brands/models are more popular and thus command higher prices? Economic Factors: Consider how broader economic factors (like inflation, fuel prices, and consumer preferences) might influence car prices in different regions.

5. Future Developments and Trends

Electric Vehicle Market: With the rise of electric vehicles, discuss how this dataset reflects the growing demand and pricing trends for EVs compared to traditional fuel cars. Impact of Technology: Consider how advancements in technology, safety features, and autonomous driving capabilities might influence future pricing.

6. Limitations of the Dataset

Data Completeness: Discuss any potential limitations in the dataset, such as missing values or biases in the data collection process. Generalization: Reflect on the ability to generalize the findings from this dataset to broader car markets or regions. Are there potential confounding factors that should be considered?

7. Potential Applications

Pricing Strategies: How can dealerships or private sellers utilize insights from this dataset to set competitive pricing? Consumer Decision-Making: Discuss how consumers can leverage this dataset to make informed purchasing decisions based on price predictions and feature evaluations.

These discussion points can help guide deeper analysis and insights into the Car Price Prediction dataset, making it a valuable resource for both academic and practical applications. If you have specific areas you want to focus on, let me know!