Pipeline Example

pipeline_example.py

transforms = []

transforms.append(
    ('select_binary', ColumnSelector(features=binary))
)

transforms.append(
    ('numeric', ExtendedPipeline([
        ('select', ColumnSelector(features=numeric)),
        ('impute', Imputer(missing_values='NaN', strategy='mean', axis=0)),
    ]))
)

for field in categorical:
    transforms.append(
        (field, ExtendedPipeline([
            ('select', ColumnSelector(features=[field])),
            ('encode', OrdinalEncoder(min_support=10))
            ])
        )
    )
    
features = FeatureUnion(transforms)