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Automobile CO2 Emissions Regression Dataset
Data Science and Analytics
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About
This dataset contains CO2 emission data for various types of cars, providing essential information for linear regression analysis. It is designed to predict carbon dioxide emissions (the target variable) based on independent features such as vehicle volume and weight. The dataset offers predicted coefficients and facilitates new data prediction, enabling the discovery of alternative target values using this robust regression model. It is expected to be updated quarterly.
Columns
- Car: The name of the car manufacturer. This column contains 36 valid entries, with 17 unique names. Mercedes and Ford each account for 14% of the entries, with the remaining 72% spread across 26 other manufacturers. The most common manufacturer is Mercedes.
- Model: The specific model name of the car. There are 36 valid entries in this column, featuring 35 unique models. Fiesta is the most common model at 6%, followed by Aygo at 3%, with 92% representing 33 other models.
- Volume: Represents the volume of fuel in the vehicle. All 36 entries are valid, with values ranging from 900 to 2500. The mean volume is approximately 1.61k, with a standard deviation of 384. Quantiles are: Min 900, 25% 1500, 50% 1600, 75% 2000, Max 2500.
- Weight: Indicates the weight of the gas. All 36 entries are valid, with weights ranging from 790 to 1746. The mean weight is approximately 1.29k, with a standard deviation of 239. Quantiles are: Min 790, 25% 1119, 50% 1330, 75% 1428, Max 1746.
- CO2: Represents the carbon dioxide emitted by the car. All 36 entries are valid, with CO2 values ranging from 90 to 120. The mean CO2 emission is 102, with a standard deviation of 7.35. Quantiles are: Min 90, 25% 98, 50% 99, 75% 105, Max 120.
Distribution
This tabular dataset is typically provided in a CSV format. It consists of 5 columns and 36 valid records, occupying a file size of 994 B. The dataset's structure is straightforward, facilitating ease of use for statistical analysis.
Usage
This dataset is ideal for conducting linear regression analysis to understand and predict automobile CO2 emissions. It can be used for developing predictive models, calculating regression coefficients, and forecasting CO2 levels for various car specifications. Its applicability extends to academic research, environmental impact assessments, and supporting data-driven policy decisions in the automotive sector.
Coverage
The data primarily focuses on automobile CO2 emissions. While specific time range details are not provided, the dataset is noted to have a quarterly expected update frequency, suggesting ongoing relevance. The geographic scope for this dataset is India, and it includes common car manufacturers such as Mercedes and Ford, alongside a wide range of other car models.
License
CC0: Public Domain
Who Can Use It
This dataset is valuable for data scientists and machine learning engineers keen on developing predictive models for environmental impact. It is also highly suitable for students and researchers undertaking projects in automotive engineering, environmental studies, and statistical modelling. Furthermore, automotive industry analysts can leverage this data for insights into vehicle performance and emissions trends.
Dataset Name Suggestions
- Automobile CO2 Emissions Regression Dataset
- Car Emissions Prediction Data (India)
- Vehicle Volume Weight CO2 Dataset
- Automotive Environmental Impact Data
- Linear Regression Car CO2 Data
Attributes
Original Data Source: Automobile CO2 Emissions Regression Dataset
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