Very simple code for comparing different R2 scores

compare_r2.py

from sklearn.datasets import make_regression
from sklearn.metrics import r2_score
import matplotlib.pyplot as plt
#%matplotlib inline

# Generate toy data
X, y, w_true = make_regression(n_samples=20, n_features=1, random_state=0, noise=1.0, coef=True)
w_bad = 0.5*w_true
w_verybad = -0.3*w_true

# Plot true data
plt.figure(figsize=(8,5))
plt.plot(X, y, '.')

# Plot a good, a bad and a very model with R2 scores
for w in [w_true, w_bad, w_verybad]:
    plt.plot(X, w*X, label="R2 Score = {:.3f}".format(r2_score(y, w*X)))
plt.legend(loc=0)
plt.show()

Output: