Yellowbrick_ML_Viz_8.py

# Getting data
import pandas as pd
df = pd.read_csv('Advertising.csv')

X = df[['TV']]
y = df['Sales']

# Create the train and test data
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=42)

# Importing ResidualsPlot visualizer
from yellowbrick.regressor import ResidualsPlot

# Importing the Linear Regression model
from sklearn.linear_model import LinearRegression

# Creating the Residuals Plot
visualizer = ResidualsPlot(LinearRegression(), hist=False)

visualizer.fit(X_train, y_train) 
visualizer.score(X_test, y_test)

# Saving plot in PNG format
visualizer.show(outpath="Residuals_Plot.png")