Completion of Python files

Code/Day 2_Simple_Linear_Regression.py

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+# Data Preprocessing
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+dataset = pd.read_csv('../datasets/studentscores.csv')
+X = dataset.iloc[ : ,   : 1 ].values
+Y = dataset.iloc[ : , 1 ].values
+
+from sklearn.cross_validation import train_test_split
+X_train, X_test, Y_train, Y_test = train_test_split( X, Y, test_size = 1/4, random_state = 0) 
+
+# Fitting Simple Linear Regression Model to the training set
+from sklearn.linear_model import LinearRegression
+regressor = LinearRegression()
+regressor = regressor.fit(X_train, Y_train)
+
+# Predecting the Result
+Y_pred = regressor.predict(X_test)
+
+# Visualising the Training results
+plt.scatter(X_train , Y_train, color = 'red')
+plt.plot(X_train , regressor.predict(X_train), color ='blue')
+
+# Visualizing the test results
+plt.scatter(X_test , Y_test, color = 'red')
+plt.plot(X_test , regressor.predict(X_test), color ='blue')
+