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Total Vehicle Sales in the United States decreased to 15.65 Million in May from 17.27 Million in April 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.
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.
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Application and use cases
1 )Market Analysis: Evaluate overall trends and regional variations in car sales to assess manufacturer performance, model preferences, and demographic insights. 2) Seasonal Patterns and Competitor Analysis: Investigate seasonal and cyclical patterns in sales. 3) Forecasting and Predictive Analysis Use historical data for forecasting and predict future market trends. Support marketing, advertising, and investment decisions based on insights. 4) Supply Chain and Inventory Optimization: Provide valuable data for stakeholders in the automotive industry.
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License information was derived automatically
Total Vehicle Sales in China decreased to 2686 Units in May from 2590000 Units in April of 2025. This dataset provides - China Total Vehicle Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.
In 2024, the auto industry in the United States sold approximately 15.9 million light vehicle units. This figure includes retail sales of about three million passenger cars and just under 12.9 million light trucks. Lower fuel consumption There are many kinds of light vehicles available in the United States. Light-duty vehicles are popular for their utility and improved fuel economy, making them an ideal choice for savvy consumers. As of Model Year 2023, the light vehicle manufacturer with the best overall miles per gallon was Kia, with one gallon of gas allowing for 30.4 miles on the road. Higher brand satisfaction When asked about light vehicle satisfaction, consumers in the United States were most satisfied with Toyota, Subaru, Tesla, and Mercedes-Benz models. Another survey conducted in 2018 and quizzing respondents on their stance regarding the leading car brands indicated that Lexus was among the most dependable brands based on the number of problems reported per 100 vehicles.
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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.
Title: 1985 Auto Imports Database
Source Information: -- Creator/Donor: Jeffrey C. Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu) -- Date: 19 May 1987 -- Sources: 1) 1985 Model Import Car and Truck Specifications, 1985 Ward's Automotive Yearbook. 2) Personal Auto Manuals, Insurance Services Office, 160 Water Street, New York, NY 10038 3) Insurance Collision Report, Insurance Institute for Highway Safety, Watergate 600, Washington, DC 20037
Past Usage: -- Kibler,~D., Aha,~D.~W., & Albert,~M. (1989). Instance-based prediction of real-valued attributes. {\it Computational Intelligence}, {\it 5}, 51--57. -- Predicted price of car using all numeric and Boolean attributes -- Method: an instance-based learning (IBL) algorithm derived from a localized k-nearest neighbor algorithm. Compared with a linear regression prediction...so all instances with missing attribute values were discarded. This resulted with a training set of 159 instances, which was also used as a test set (minus the actual instance during testing). -- Results: Percent Average Deviation Error of Prediction from Actual -- 11.84% for the IBL algorithm -- 14.12% for the resulting linear regression equation
Relevant Information: -- Description This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as compared to other cars. The second rating corresponds to the degree to which the auto is more risky than its price indicates. Cars are initially assigned a risk factor symbol associated with its price. Then, if it is more risky (or less), this symbol is adjusted by moving it up (or down) the scale. Actuarians call this process "symboling". A value of +3 indicates that the auto is risky, -3 that it is probably pretty safe.
The third factor is the relative average loss payment per insured vehicle year. This value is normalized for all autos within a particular size classification (two-door small, station wagons, sports/speciality, etc...), and represents the average loss per car per year.
-- Note: Several of the attributes in the database could be used as a "class" attribute.
Number of Instances: 205
Number of Attributes: 26 total -- 15 continuous -- 1 integer -- 10 nominal
Attribute Information:
Attribute: Attribute Range:
Missing Attribute Values: (denoted by "?") Attribute #: Number of instances missing a value:
Data files containing detailed information about vehicles in the UK are also available, including make and model data.
Some tables have been withdrawn and replaced. The table index for this statistical series has been updated to provide a full map between the old and new numbering systems used in this page.
Tables VEH0101 and VEH1104 have not yet been revised to include the recent changes to Large Goods Vehicles (LGV) and Heavy Goods Vehicles (HGV) definitions for data earlier than 2023 quarter 4. This will be amended as soon as possible.
Overview
VEH0101: https://assets.publishing.service.gov.uk/media/6846e8dc57f3515d9611f119/veh0101.ods">Vehicles at the end of the quarter by licence status and body type: Great Britain and United Kingdom (ODS, 151 KB)
Detailed breakdowns
VEH0103: https://assets.publishing.service.gov.uk/media/6846e8dcd25e6f6afd4c01d5/veh0103.ods">Licensed vehicles at the end of the year by tax class: Great Britain and United Kingdom (ODS, 33 KB)
VEH0105: https://assets.publishing.service.gov.uk/media/6846e8dd57f3515d9611f11a/veh0105.ods">Licensed vehicles at the end of the quarter by body type, fuel type, keepership (private and company) and upper and lower tier local authority: Great Britain and United Kingdom (ODS, 16.3 MB)
VEH0206: https://assets.publishing.service.gov.uk/media/6846e8dee5a089417c806179/veh0206.ods">Licensed cars at the end of the year by VED band and carbon dioxide (CO2) emissions: Great Britain and United Kingdom (ODS, 42.3 KB)
VEH0601: https://assets.publishing.service.gov.uk/media/6846e8df5e92539572806176/veh0601.ods">Licensed buses and coaches at the end of the year by body type detail: Great Britain and United Kingdom (ODS, 24.6 KB)
VEH1102: https://assets.publishing.service.gov.uk/media/6846e8e0e5a089417c80617b/veh1102.ods">Licensed vehicles at the end of the year by body type and keepership (private and company): Great Britain and United Kingdom (ODS, 146 KB)
VEH1103: https://assets.publishing.service.gov.uk/media/6846e8e0e5a089417c80617c/veh1103.ods">Licensed vehicles at the end of the quarter by body type and fuel type: Great Britain and United Kingdom (ODS, 992 KB)
VEH1104: https://assets.publishing.service.gov.uk/media/6846e8e15e92539572806177/veh1104.ods">Licensed vehicles at the end of the
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Total Vehicle Sales in Thailand decreased to 47190 Units in April from 55793 Units in March of 2025. This dataset provides - Thailand Total Vehicle Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Car Registrations in Canada increased to 195659 Units in April from 189046 Units in March of 2025. This dataset provides - Canada Total New Cars - actual values, historical data, forecast, chart, statistics, economic calendar and news.
In financial year 2024, Maruti Suzuki sold approximately 1.6 million passenger cars across India. This made it the leading car manufacturer in terms of car sales in India, followed distantly by Hyundai and Tata. The automobile sector across India saw recovering from the impact of the coronavirus (COVID-19) pandemic in the same year. Is the Indian automobile market in trouble? There were more than 326 million vehicles registered in India in the financial year 2020. Vehicle registrations grew at a compound annual growth rate of over 10 percent between 2017 and 2020. However, due to economic slowdown, the introduction of new Bharat Stage Emission Standards VI (BS-VI) in 2019, and the impact of the coronavirus pandemic, the domestic sales of vehicles have been declining since the financial year 2020 for two consecutive years. This continued until the financial year 2023. New trend – electric vehicles With strong government support through policy initiatives such as the National Electric Mobility Mission Plan 2020 introduced in 2013, Faster Adoption and Manufacturing of (Hybrid &) Electric Vehicles (FAME) in 2015, and further FAME phase II in 2019, India was aiming to achieve 30 percent private electric vehicle ownership. As two-wheelers were the most popular types of automobiles for the last decade, in the financial year 2023, the majority of electric vehicles sold in India were also two-wheelers. The demand for electric vehicles is expected to rise significantly in the future.
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Key information about India Motor Vehicle Sales: Passenger Cars
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This dataset was collected by me from a homework for study and practice. Dataset contains 50618 rows and 5 variables: Name: Name of car Production Year: Year of production Price: Seller's price Color: Color of the car Type: Type of the car
I hope this dataset can be useful for you!
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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.
Motor vehicle sales grew by some **** percent worldwide between 2022 and 2023. Passenger vehicles increased by around **** percent compared to the previous year when some **** million cars were sold worldwide. The current state of the market In 2023, motor vehicle sales reached over **** million units worldwide. China was the largest automobile market worldwide, making up close to **** million of the new car registrations that same year. The United States and Europe ranked second and third, with light vehicle sales reaching approximately **** million units in the U.S. market. The German-based Volkswagen Group and Japanese Toyota Motor were the global leading automakers, with revenues reaching around ***** and ***** billion U.S. dollars respectively as of May 2024. The path to recovery The automotive chip shortage led to around **** million vehicles being cut from worldwide production in 2021, and forecasts estimate that these disruptions in the automotive supply chain will contribute to the removal of another ***** million units from production in 2022. However, despite these challenges, the demand for passenger cars increased in 2021 and 2022, as car sales slowly started to increase. This is partly due to consumers' interest in electric vehicles. Autonomous,electrified, and battery electric vehicles are also forecast to gain popularity in the next decades. Electrified vehicles are projected to make up close to ********* of car sales worldwide by 2025. By 2040, China is forecast to be one of the largest market for autonomous vehicle sales.
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Electric Car Registrations in China increased to 1307000 Units in May from 1226000 Units in April of 2025. This dataset includes a chart with historical data for China Electric Car Registrations.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Key information about United States Motor Vehicle Sales: Passenger Cars
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
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This dataset is not of my own but data that I have downloaded from another Kaggle user in order to improve my skills with r programming. I have decided to use this particular dataset to work with as I have a passion for cars and thought by working with data that I am passionate about I will be more focused to find trends within this data set that may pique my interest.
This is a vehicle sales dataset with the purpose of capturing all sales data of each vehicle and all its variables upon sales as listed below.
Year, make, model, trim, body type, transmission type, VIN (Vehicle Identification Number), state of registration, condition rating, odometer reading, exterior and interior colours, seller information, Manheim Market Report (MMR) values, selling prices, and sale dates.
I Hope to find insight relationships within this data set and look forward to what the Kaggle community will say once i have completed this analysis. Insightful criticism is always welcomed.
SpaceKnow uses satellite (SAR) data to capture activity in electric vehicles and automotive factories.
Data is updated daily, has an average lag of 4-6 days, and history back to 2017.
The insights provide you with level and change data that monitors the area which is covered with assembled light vehicles in square meters.
We offer 3 delivery options: CSV, API, and Insights Dashboard
Available companies Rivian (NASDAQ: RIVN) for employee parking, logistics, logistic centers, product distribution & product in the US. (See use-case write up on page 4) TESLA (NASDAQ: TSLA) indices for product, logistics & employee parking for Fremont, Nevada, Shanghai, Texas, Berlin, and Global level Lucid Motors (NASDAQ: LCID) for employee parking, logistics & product in US
Why get SpaceKnow's EV datasets?
Monitor the company’s business activity: Near-real-time insights into the business activities of Rivian allow users to better understand and anticipate the company’s performance.
Assess Risk: Use satellite activity data to assess the risks associated with investing in the company.
Types of Indices Available Continuous Feed Index (CFI) is a daily aggregation of the area of metallic objects in square meters. There are two types of CFI indices. The first one is CFI-R which gives you level data, so it shows how many square meters are covered by metallic objects (for example assembled cars). The second one is CFI-S which gives you change data, so it shows you how many square meters have changed within the locations between two consecutive satellite images.
How to interpret the data SpaceKnow indices can be compared with the related economic indicators or KPIs. If the economic indicator is in monthly terms, perform a 30-day rolling sum and pick the last day of the month to compare with the economic indicator. Each data point will reflect approximately the sum of the month. If the economic indicator is in quarterly terms, perform a 90-day rolling sum and pick the last day of the 90-day to compare with the economic indicator. Each data point will reflect approximately the sum of the quarter.
Product index This index monitors the area covered by manufactured cars. The larger the area covered by the assembled cars, the larger and faster the production of a particular facility. The index rises as production increases.
Product distribution index This index monitors the area covered by assembled cars that are ready for distribution. The index covers locations in the Rivian factory. The distribution is done via trucks and trains.
Employee parking index Like the previous index, this one indicates the area covered by cars, but those that belong to factory employees. This index is a good indicator of factory construction, closures, and capacity utilization. The index rises as more employees work in the factory.
Logistics index The index monitors the movement of materials supply trucks in particular car factories.
Logistics Centers index The index monitors the movement of supply trucks in warehouses.
Where the data comes from: SpaceKnow brings you information advantages by applying machine learning and AI algorithms to synthetic aperture radar and optical satellite imagery. The company’s infrastructure searches and downloads new imagery every day, and the computations of the data take place within less than 24 hours.
In contrast to traditional economic data, which are released in monthly and quarterly terms, SpaceKnow data is high-frequency and available daily. It is possible to observe the latest movements in the EV industry with just a 4-6 day lag, on average.
The EV data help you to estimate the performance of the EV sector and the business activity of the selected companies.
The backbone of SpaceKnow’s high-quality data is the locations from which data is extracted. All locations are thoroughly researched and validated by an in-house team of annotators and data analysts.
Each individual location is precisely defined so that the resulting data does not contain noise such as surrounding traffic or changing vegetation with the season.
We use radar imagery and our own algorithms, so the final indices are not devalued by weather conditions such as rain or heavy clouds.
→ Reach out to get a free trial
Use Case - Rivian:
SpaceKnow uses the quarterly production and delivery data of Rivian as a benchmark. Rivian targeted to produce 25,000 cars in 2022. To achieve this target, the company had to increase production by 45% by producing 10,683 cars in Q4. However the production was 10,020 and the target was slightly missed by reaching total production of 24,337 cars for FY22.
SpaceKnow indices help us to observe the company’s operations, and we are able to monitor if the company is set to meet its forecasts or not. We deliver five different indices for Rivian, and these indices observe logistic centers, employee parking lot, logistics, product, and prod...
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Total Vehicle Sales in Chile decreased to 24337 Units in May from 26132 Units in April of 2025. This dataset provides - Chile Total Vehicle Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Total Vehicle Sales in the United States decreased to 15.65 Million in May from 17.27 Million in April 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.