featuretools.primitives.MultiplyNumericBoolean#

class featuretools.primitives.MultiplyNumericBoolean[source]#

Performs element-wise multiplication of a numeric list with a boolean list.

Description:: Given a list of numeric values X and a list of boolean values Y, return the values in X where the corresponding value in Y is True.

Examples

>>> import pandas as pd
>>> multiply_numeric_boolean = MultiplyNumericBoolean()
>>> multiply_numeric_boolean([2, 1, 2], [True, True, False]).tolist()
[2, 1, 0]
>>> multiply_numeric_boolean([2, None, None], [True, True, False]).tolist()
[2.0, nan, nan]
>>> multiply_numeric_boolean([2, 1, 2], pd.Series([True, True, pd.NA], dtype="boolean")).tolist()
[2, 1, <NA>]

__init__()#

Methods

`__init__`()
`flatten_nested_input_types`(input_types)	Flattens nested column schema inputs into a single list.
`generate_name`(base_feature_names)
`generate_names`(base_feature_names)
`get_args_string`()
`get_arguments`()
`get_description`(input_column_descriptions[, ...])
`get_filepath`(filename)
`get_function`()

Attributes

`base_of`
`base_of_exclude`
`commutative`
`compatibility`	Additional compatible libraries
`default_value`	Default value this feature returns if no data found.
`description_template`
`input_types`	woodwork.ColumnSchema types of inputs
`max_stack_depth`
`name`	Name of the primitive
`number_output_features`	Number of columns in feature matrix associated with this feature
`return_type`	ColumnSchema type of return
`series_library`
`stack_on`
`stack_on_exclude`
`stack_on_self`
`uses_calc_time`
`uses_full_dataframe`