Practical demonstration of using LOF to drop outlier rows

LOF_outliers.py

# Import the required library
from sklearn.neighbors import LocalOutlierFactor

# define LOF class
lof = LocalOutlierFactor() # consider playing around with 'n_neighbors' parameter

# predict whether the numerical columns are outlier or not
yhat = lof.fit_predict(X_train)

# select all rows that are not outliers
mask = yhat != -1
X_train_clean = X_train[mask]

# Don't forget to apply the mask to your target variable as well