evalml.pipelines.components.DateTimeFeaturizer

class evalml.pipelines.components.DateTimeFeaturizer(features_to_extract=None, encode_as_categories=False, random_state=None, random_seed=0, **kwargs)

Transformer that can automatically featurize DateTime columns.

name = 'DateTime Featurization Component'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'encode_as_categories': False, 'features_to_extract': ['year', 'month', 'day_of_week', 'hour']}

Instance attributes

needs_fitting
parameters	Returns the parameters which were used to initialize the component

Methods:

__init__	Extracts features from DateTime columns
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits component to data
fit_transform	Fits on X and transforms X
get_feature_names	Gets the categories of each datetime feature.
load	Loads component at file path
save	Saves component at file path
transform	Transforms data X by creating new features using existing DateTime columns, and then dropping those DateTime columns

Class Inheritance

evalml.pipelines.components.DropNullColumns.transform evalml.pipelines.components.DateTimeFeaturizer.__init__