aditya17-09 / co-2

CO2 Emission Simple Multivariate and Simple Univariate Linear Regression

This repository contains the code and data for performing simple multivariate and simple univariate linear regression on CO2 emission data. The goal of this analysis is to explore the relationship between CO2 emissions and various factors such as engine size, number of cylinders, and fuel consumption.

Dataset:

The dataset used in this analysis is the "Fuel Consumption Ratings" dataset provided by Natural Resources Canada. This dataset contains information on fuel consumption and CO2 emissions for various vehicles, including their engine size, number of cylinders, and other features.

Files:

-->CO2 Emission Simple Multivariate Linear Regression.ipynb: Jupyter notebook containing the code for performing simple multivariate linear regression on the CO2 emission data.

-->CO2 Emission Simple Univariate Linear Regression.ipynb: Jupyter notebook containing the code for performing simple univariate linear regression on the CO2 emission data.

-->FuelConsumption.csv: CSV file containing the dataset used in this analysis.

Dependencies:

This analysis was performed using Python 3. The following Python libraries are required to run the code:

numpy, pandas, matplotlib, scikit-learn

Usage: To use this code, simply clone the repository and open the desired Jupyter notebook file in Jupyter Notebook or JupyterLab. The code is commented to explain each step of the analysis.

The FuelConsumption.csv file contains the data used in this analysis and should be kept in the same directory as the Jupyter notebooks.