# Data Preprocessing Template

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

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

# Splitting the dataset into the Training set 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
# most of implementations apply it automatically
# from sklearn.preprocessing import StandardScaler
# sc_X = StandardScaler()
# X_train = sc_X.fit_transform(X_train)
# X_test = sc_X.transform(X_test)
