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 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.

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.

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.

Average car price in Brazil

Abou the data

Data extracted from FIPE.

Every observation (row) corresponds to a average car price, calculated to a month of a year of reference. In other words, in a year (year_of_reference) there are 12 observations related to the same car, however avg_price_brl might differ.

The variables fuel, gear and engine_size were extracted from values of column model, as in original there is no column dedicated to those values. Since some values for model don't contain the information of engine size, this dataset doesn't contain the whole data from FIPE's original. Additionally, if 'Aut.' is not present in model, the car is assumed to be manual.

The prices are calculated by FIPE and they're here as original (in BRL).

FIPE updates the information on a monthly basis. Here, the referred month is given as month_of_reference, as the corresponding year has variable named as year_of_reference

The FIPE codes (fipe_codes) are the model identifier used in FIPE webpage.

Variables

• year_of_reference: year of reference of the observation, i.e., the year the data corresponds to.
• moth_of_reference: month of reference of the observation, i.e., the month the data corresponds to. The average price is calculated by FIPE each month.
• fipe_code: unique id corresponding to a model for easy search on FIPE webpage.
• authentication: unique code that authenticates the consult in FIPE's site.
• brand: car's make.
• model: a description of the car containing the name and other descriptive information, as provided in FIPE table.
• fuel: fuel used by the car. Some of gas cars are actually alcohol and gas (totalflex), which is common in Brazil.
• gear: the way gears are shifted.
• engine_size: Engine size measured in cubic centimeters.
• year_model: those values corresponds to the year of reference, and may not be the same of the year of manufacture, which in case will corresponds to a year before year_model. Observations with year_model = year_of_reference mean the car is brand new for that year of reference, i.e., a 2021 car with year_of_reference = 2021 and moth_of_reference = July mean that the observation (mainly the average price) corresponds to a brand new car in the year of 2021, of the month of July. The same model may have a different average price for different month.
• avg_price_brl: average car's price, as measured by FIPE, in BRL.

- (variable deleted in Version 2).

Questions

Here are some questions that may be used as starting point of analysis.

• How average prices depend on car's age?
• How the engine size contribute to the average price?
• Can FIPE's prices be used to predict car prices?
• Gather some data from real stores. Can you compute you own average? How's it different from FIPE's?
• Build a time series and make explore them accordingly to engine size and gear type.
• Scale prices with Brazil's minimum wage in order make analysis period wise.`

🚗 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 !!

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.

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.

Switzerland had the highest price tags on new passenger cars sold in 2020, overtaking Norway for the first time in five years. Swiss people had to dig deeper into their pockets than any of their European neighbors, with prices roughly 15,000 euros higher than the EU-28 average. Reasons for automobiles being so costly in Switzerland are partly due to tax rates, which are set by each canton based on a set of varying criteria including but not limited to vehicle weight, powertrain, and CO2 emissions. These incentives contribute to making larger, heavier vehicles using petrol and diesel engines more expensive. The only vehicles exempt from taxes in selected cantons were electric cars. Electric vehicles are extremely popular in Norway, second in the ranking in terms of average vehicle price, in parts due to the VAT and tolls exemptions for electric vehicles in the country. Norwegian buyers are able to spend more on high-tech models.

Car tax rates in Nordic countries higher on average
Other European countries with a 25 percent tax rate on acquisition are Croatia, Denmark and Sweden, while those in Hungary even exceeded Norwegian rates by two percent. As seen in this statistic higher tax rates on passenger cars translates to higher prices overall. Sweden and Denmark both appeared in the top seven most expensive car buying countries. Hence, in terms of volume of new car registrations, Northern European countries trailed behind not only their more populous neighbors, but also other smaller countries where tax rates were lower.

Prices for passenger cars to stay stable
Prices for passenger cars were forecast to stay relatively stable in the next three years, with only slight increases expected. Luxury cars were the only group where price change was estimated to be more prominent.

🚗 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! 💡

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

Graph and download economic data for Consumer Price Index for All Urban Consumers: New Vehicles in U.S. City Average (CUSR0000SETA01) from Jan 1953 to Sep 2025 about vehicles, urban, new, consumer, CPI, inflation, price index, indexes, price, and USA.

This dataset contains detailed information about used cars, including key features such as make, model, year of manufacture, engine size, mileage, fuel type, transmission, and price. It is designed to support data analysis, visualization, and machine learning tasks—particularly regression models aimed at predicting car prices.

The Price column is the target variable, and all other features can be used as inputs to estimate the value of a vehicle based on its specifications and condition.

This dataset is suitable for beginner and intermediate data science projects, including:

1-Exploratory Data Analysis (EDA)

2-Feature engineering

3-Regression modeling

4-Model evaluation and comparison

The Feature :

1-Make: The manufacturer or brand of the vehicle (e.g., Toyota, BMW, Ford).

2-Model: The variant or trim level of the vehicle, labeled as 'a', 'b', 'c', 'd', or 'e'. These may represent different equipment levels, features, or configurations of the same car model.

2-Year: The year the car was manufactured or released.

3-Engine Size :The engine capacity in liters (L), indicating its total displacement and general performance level.

4-Mileage: The total distance the car has been driven, typically measured in kilometers or miles.

5-Fuel Type :The type of fuel the vehicle uses, such as Petrol, Diesel, Hybrid, or Electric.

6-Transmission :The type of gearbox system used in the vehicle, commonly Manual or Automatic.

7-Price(target ):The selling price of the vehicle, usually in the local currency. This is the target variable, used for prediction in regression models to estimate car value based on other features.

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.

The average list price for used vehicles in the United States reached some ****** U.S. dollars in June 2023. This was a year-on-year decrease of around *** percent of the June 2022 average, which stood at under ****** U.S. dollars. Used cars recorded an overall increase in prices and a decrease in more affordable stocks as a consequence of the global chip shortage which put the automotive industry at a standstill, affecting the production of new vehicles.

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)

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.

The average for 2021 based on 165 countries was 108.07 index points. The highest value was in Singapore: 355.77 index points and the lowest value was in Syria: 58.27 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

The 'Used Car Prices YoY' in the USA measures the year-over-year change in the prices of used vehicles.-2025-01-08

The 'Used Car Prices YoY' in the USA measures the year-over-year change in the prices of used vehicles.-2025-12-05