evalml.pipelines.components.SelectColumns

class evalml.pipelines.components.SelectColumns(columns=None, random_seed=0, **kwargs)

Selects specified columns in input data.

name = 'Select Columns Transformer'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'columns': None}

Instance attributes

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

Methods:

__init__	Initalizes an transformer that drops specified columns in input data.
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits the transformer by checking if column names are present in the dataset.
fit_transform	Fits on X and transforms X
load	Loads component at file path
save	Saves component at file path
transform	Transforms data X by selecting columns.

Class Inheritance

evalml.pipelines.components.DropColumns.transform evalml.pipelines.components.SelectColumns.__init__