bank_marketing_label_only.py

# Label Encode instead of dummy variables

mappings = []

from sklearn.preprocessing import LabelEncoder

label_encoder = LabelEncoder()

label_df = df.drop('y', axis=1)
for i, col in enumerate(label_df):
    if label_df[col].dtype == 'object':
        label_df[col] = label_encoder.fit_transform(np.array(label_df[col].astype(str)).reshape((-1,)))
        mappings.append(dict(zip(label_encoder.classes_, range(1, len(label_encoder.classes_)+1))))