TheilSen1.py

# Set auto reload
%reload_ext autoreload
%autoreload 2

# Import libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

from sklearn.datasets import make_regression
from sklearn.linear_model import LinearRegression, TheilSenRegressor

# Config 
%config InlineBackend.figure_format = 'retina' #Retina display
plt.style.use('seaborn-deep') #Plot style

# Create regression data
X, y = make_regression(
    n_samples = 150,
    n_features = 1,
    noise = 5
)

# Add outlier
for j in range(15):
    X = np.append(
        X, np.random.choice(X.flatten())
    )
    y = np.append(
        y, np.random.choice(y.flatten())
    )

X = X.reshape(-1,1)
y = y.reshape(-1,1)