# Create new features df['avg_sales_per_customer'] = df['sales'] / df['customers'] df['sales_growth_rate'] = df['sales'].pct_change()
# Make predictions on testing set y_pred = model.predict(X_test) building data science solutions with anaconda pdf
from sklearn.metrics import mean_squared_error, r2_score building data science solutions with anaconda pdf