ourlifeinkodaks / carbon-prediction Goto Github PK

In this code, we use scikit-learn to implement simple linear regression. We use a dataset that is related to fuel consumption and Carbon dioxide emission of cars. Then, we split our data into training and test sets, create a model using training set, Evaluate your model using test set, and finally use model to predict unknown value


Importing Needed packages:

import matplotlib.pyplot as plt
import pandas as pd
import pylab as pl
import numpy as np
(optional) %matplotlib inline (IPython required)

Understanding the Data:

FuelConsumption.csv:
We have used a fuel consumption dataset, FuelConsumption.csv, which contains model-specific fuel consumption ratings and estimated carbon dioxide emissions for new light-duty vehicles for retail sale in Canada. 

MODELYEAR e.g. 2014
MAKE e.g. Acura
MODEL e.g. ILX
VEHICLE CLASS e.g. SUV
ENGINE SIZE e.g. 4.7
CYLINDERS e.g 6
TRANSMISSION e.g. A6
FUEL CONSUMPTION in CITY(L/100 km) e.g. 9.9
FUEL CONSUMPTION in HWY (L/100 km) e.g. 8.9
FUEL CONSUMPTION COMB (L/100 km) e.g. 9.2
CO2 EMISSIONS (g/km) e.g. 182 --> low --> 0