from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn import metrics

# Step 1: split your features and labels into train and test data 
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# Step 2: Define which model you want to use 
model = LinearRegression()

# Step 3: Fit the model to your training data 
model.fit(X_train, y_train)

# Step 4: Obtain model predictions from your test data
y_predicted = model.predict(X_test)

# Step 5: Compare y_test to predictions and obtain performance metrics
print (metrics.r2_score(y_test, y_predicted))

0.821206237313