#	Data preprocessing

#Importing the libraries
import numpy as np 
import matplotlib.pyplot as plt
import pandas as pd 

#Import the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[: , :-1].values
y = dataset.iloc[: , -1].values

#Splitting the dataset into training and test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.2, random_state = 0)

##Feature scaling
#from sklearn.preprocessing import StandardScaler
#sc_X = StandardScaler()
#X_train = sc_X.fit_transform(X_train)
#X_test = sc_X.transform(X_test)



