This dataset provides comprehensive information about used cars available for sale in the United States. It includes detailed data on various aspects of each vehicle, making it a valuable resource for car buyers, sellers, and data enthusiasts. The dataset contains the following key attributes:

• Brand: The brand or manufacturer of the car.
• Model: The specific model of the car.
• Mileage: The number of miles the car has been driven.
• Year: The manufacturing year of the car.
• Status: Indicates whether the car is new, used, or certified pre-owned.
• Dealer: Information about the dealer or seller offering the car.
• Price: The listed price of the car in USD.

This dataset is ideal for data analysis, machine learning projects, and market research related to the used car industry in the United States. Whether you are interested in predicting car prices, understanding market trends, or simply searching for your next vehicle, this dataset provides a wealth of information to explore.

Data Source: More info on my GitHub repository

Data Format: CSV

Detailed Dataset Description: Car Sales Transactional Data This dataset provides a rich, multi-dimensional view of individual car sales transactions, capturing valuable information across customer demographics, car specifications, pricing metrics, payment details, sales performance, and seasonal or regional context. Each row in the dataset represents a single car sale transaction, allowing for granular-level analysis of how various factors influence profitability, sales trends, and customer behavior.

📅 Date & Temporal Context Date: The exact date of the transaction, allowing daily trend analysis.

Sale Year, Month, Quarter, Day of Week, and Season: These columns offer temporal segmentation that helps identify seasonal patterns, monthly performance, and weekday vs weekend trends.

🧑‍💼 Salesperson and Customer Information Salesperson: Identifies the individual responsible for the sale, useful for tracking salesperson performance, commission analysis, and productivity metrics.

Customer Name, Age, and Gender: Offers demographic insights, enabling segmentation by age group and gender, and understanding customer preferences in vehicle types and pricing.

🚗 Vehicle Details Car Make and Model: Specifies the brand and specific vehicle model sold.

Car Year: Indicates the model year of the vehicle, helpful in analyzing the popularity of newer vs older models.

💵 Financial and Sales Metrics Quantity: Number of cars sold in the transaction (typically 1, but can vary in business fleet cases).

Sale Price and Cost: Gross sale price and internal cost incurred by the dealership.

Profit: Computed as the difference between sale price and cost, giving direct insight into transaction-level profitability.

Discount: Shows the discount offered as a decimal (e.g., 0.05 = 5%), aiding in understanding the impact of promotions on sales.

💳 Payment & Incentive Structure Payment Method: Indicates how the customer paid (e.g., Cash, Loan, Credit), helping identify payment preferences over time or across customer types.

Commission Rate & Commission Earned: Details the salesperson's incentive structure and earnings from the sale, supporting analysis of commission efficiency, reward optimization, and employee motivation.

🌎 Geographic Coverage Sales Region: Highlights the physical region where the sale occurred (e.g., Alaska), allowing for regional performance comparison, mapping in BI tools, and assessing market penetration across different areas.

Use Cases and Applications This dataset can be effectively used for:

Business Intelligence Dashboards (e.g., Tableau, Power BI)

Sales & Profitability Analysis

Customer Demographics and Segmentation

Payment Method Trends

Salesperson Performance Monitoring

Seasonal Demand Forecasting

Regional Sales Comparisons

Commission Strategy Optimization

Its wide coverage across multiple dimensions makes it ideal for predictive modeling, trend visualization, and data storytelling in sales, marketing, and operations

Total Vehicle Sales in the United States decreased to 15.30 Million in October from 16.40 Million in September of 2025. This dataset provides the latest reported value for - United States Total Vehicle Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The U.S. auto industry sold nearly ************* cars in 2024. That year, total car and light truck sales were approximately ************ in the United States. U.S. vehicle sales peaked in 2016 at roughly ************ units. Pandemic impact The COVID-19 pandemic deeply impacted the U.S. automotive market, accelerating the global automotive semiconductor shortage and leading to a drop in demand during the first months of 2020. However, as demand rebounded, new vehicle supply could not keep up with the market. U.S. inventory-to-sales ratio dropped to its lowest point in February 2022, as Russia's war on Ukraine lead to gasoline price hikes. During that same period, inflation also impacted new and used car prices, pricing many U.S. consumers out of a market with increasingly lower car stocks. Focus on fuel economy The U.S. auto industry had one of its worst years in 1982 when customers were beginning to feel the effects of the 1973 oil crisis and the energy crisis of 1979. Since light trucks would often be considered less fuel-efficient, cars accounted for about ** percent of light vehicle sales back then. Thanks to improved fuel economy for light trucks and cheaper gas prices, this picture had completely changed in 2020. That year, prices for Brent oil dropped to just over ** U.S. dollars per barrel. The decline occurred in tandem with lower gasoline prices, which came to about **** U.S. dollars per gallon in 2020 - and cars only accounted for less than one-fourth of light vehicle sales that year. Four years on, prices are dropping again, after being the highest on record since 1990 in 2022.

The Car Sales Dataset is a collection of data that contains information on various car models sold in the market. The dataset includes variables such as the price of the car in thousands of dollars, engine size, horsepower, fuel efficiency, and sales. 1. Price_in_thousands: This variable represents the price of the car in thousands of dollars, which is a measure of the car's cost. 2. Engine_size: This variable represents the size of the engine in cubic centimeters, which is a measure of the car's power. 3. Horsepower: This variable represents the power of the car's engine in horsepower, which is a measure of the car's ability to accelerate and maintain speed. 4. Fuel_efficiency: This variable represents the number of miles per gallon (mpg) that the car can travel on a single gallon of fuel, which is a measure of the car's fuel efficiency. 5. Sales: This variable represents the number of units of the car sold in a given period, which is a measure of the car's popularity and demand in the market.

Overall, this dataset can be used to analyze the relationships between the different variables and to predict the sales of a car based on its price, engine size, horsepower, and fuel efficiency. It can be helpful for businesses and consumers alike in making informed decisions about buying and selling cars.

The number of new and used vehicles and the sales dollars respectively sold by month. MDOT MVA’s Customer Connect modernization project, implemented in July 2020, has increased the amount of data that is collected and used to calculate car sales. This data is updated in real time and may fluctuate based on external factors, including electronic submissions from dealers and other vendors.

This dataset contains raw data on car sales from Cars.com. It includes detailed information about each car, such as the model, condition, mileage, year of production, dealer name, as well as total and monthly prices. The data was extracted from 500 pages of the site and is stored in its raw format, ready for cleaning and further analysis. This dataset is intended for research and analysis purposes in the automotive industry, enabling market studies, price forecasting, and trend analysis.

Autos include all passenger cars, including station wagons. The U.S. Bureau of Economic Analysis releases auto and truck sales data, which are used in the preparation of estimates of personal consumption expenditures.

Number of units and total sales of new motor vehicles by vehicle type and origin of manufacture, monthly.

Total Vehicle Sales in China increased to 3322000 Units in October from 3226000 Units in September of 2025. This dataset provides - China Total Vehicle Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset included Information about 43 brands, and 445 models of vehicles for sale in the US. The period is from 2013 to 2022 Data source: www.goodcarbadcar.net, www.marklines.com/en/vehicle_sales/index

Worldwide car sales grew to around ** million automobiles in 2024, up from around **** million units in 2023. Throughout 2020 and 2021, the sector experienced a downward trend on the back of a slowing global economy, while COVID-19 and the Russian war on Ukraine contributed to shortages in the automotive semiconductor industry and further supply chain disruptions in 2022. Despite these challenges, 2023 and 2024 sales surpassed pre-pandemic levels and are forecast to keep rising through 2025 and 2026. Covid-19 hits car demand It had been estimated pre-pandemic that international car sales were on track to reach ** million. While 2023 sales are still far away from that goal, this was the first year were car sales exceeded pre-pandemic values. The automotive market faced various challenges in 2023, including supply shortages, automotive layoffs, and strikes in North America. However, despite these hurdles, the North American market was among the fastest-growing regions in 2024, along with Eastern Europe and Asia, as auto sales in these regions increased year-on-year. Chinese market recovers After years of double-digit growth, China's economy began to lose steam in 2022, and recovery has been slow through 2023. China was the largest automobile market based on sales with around **** million units in 2023. However, monthly car sales in China were in free-fall in April 2022 partly due to shortages, fears over a looming recession, and the country grappling with the COVID-19 pandemic. By June of that same year, monthly sales in China were closer to those recorded in 2021.

Total Vehicle Sales in Russia decreased to 93791 Units in May from 105939 Units in April of 2025. This dataset provides - Russia Total Vehicle Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Dear Kagglers. Dataset contains three csv files , 1st file for Commercial vehicles sales across countries from 2019 to 2023 2nd file for Commercial vehicles sales across countries from 2019 to 2023 3rd file for combined data of above two files. Feel free to ask questions , if you Need any specific type of data let me know i will upload.

Car Registrations in Canada increased to 168731 Units in September from 166524 Units in August of 2025. This dataset provides - Canada Total New Cars - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Colorado Motor Vehicle Sales Data

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1937611%2F154e9e08b0b0e6e2bf21422aecdc5425%2F_01d75451-99b3-4e23-9cdb-e728dddaee95.jpeg?generation=1716288460302892&alt=media" alt="">

Description

This dataset contains information on motor vehicle sales in various counties across Colorado, segmented by year and quarter. The data is useful for analyzing trends in vehicle sales, understanding the economic impact of automotive transactions, and making informed decisions in related business or policy planning.

Columns

• Year: The calendar year in which the sales data was recorded.
• Quarter: The quarter of the year during which the sales were made. The quarters are divided as follows:
  • Q1: January to March
  • Q2: April to June
  • Q3: July to September
  • Q4: October to December
• County: The name of the county in Colorado where the sales were recorded.
• Sales: The total dollar amount of motor vehicle sales in the specified county and quarter.

Use Cases

• Economic Analysis: Track the economic health and trends in the automotive market within Colorado.
• Market Research: Identify sales patterns and market demands in different counties.
• Policy Making: Inform decisions on automotive industry regulations and infrastructure planning.

File Format

The dataset is available in CSV format, making it easy to import into various data analysis tools and software. The CSV file might be named colorado_motor_vehicle_sales.csv.

The data set has the most number of nulls in the Transmission column with over 11% of the total rows as nulls with 550k total rows if you remove nulls and garbage values the dataset comes to 440k usable rows. Which is still a lot! I have a notebook submission worked on the clean data. If anyone wants the cleaned data feel free to send me an email (krishanu2000@gmail.com) I'll send it to you!

Link to original dataset: https://www.kaggle.com/datasets/syedanwarafridi/vehicle-sales-data/

Column Details: Vehicle Details: Includes specific information about each vehicle, such as its make, model, trim, and manufacturing year.

Transaction Information: Provides insights into the sales transactions, including selling prices and sale dates.

Market Trends: MMR values offer an estimate of the market value of each vehicle, allowing for analysis of market trends and fluctuations.

Condition and Mileage: Contains data on the condition of the vehicles as well as their odometer readings, enabling analysis of how these factors influence selling prices.

This dataset provides values for TOTAL VEHICLE SALES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Quarterly data on vehicle registration by fuel type, vehicle type and number of vehicles, Canada, the provinces, census metropolitan areas and census sub-divisions.