nlp_primitives.PartOfSpeechCount#

class nlp_primitives.PartOfSpeechCount[source]#

Calculates the occurences of each different part of speech.

Description:

Given a list of strings, categorize each word in the string as a different part of speech, and return the total count for each of 15 different categories of speech.

If a string is missing, return NaN.

Examples

>>> x = ['He was eating cheese', '']
>>> part_of_speech_count = PartOfSpeechCount()
>>> part_of_speech_count(x).tolist()
[[0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [1.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [1.0, 0.0], [0.0, 0.0]]
__init__()[source]#

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