nlp_primitives.PolarityScore#

class nlp_primitives.PolarityScore[source]#

Calculates the polarity of a text on a scale from -1 (negative) to 1 (positive)

Description:

Given a list of strings assign a polarity score from -1 (negative text), to 0 (neutral text), to 1 (positive text). The functions returns a score for every given piece of text. If a string is missing, return ‘NaN’

Examples

>>> x = ['He loves dogs', 'She hates cats', 'There is a dog', '']
>>> polarity_score = PolarityScore()
>>> polarity_score(x).tolist()
[0.808, -0.787, 0.0, 0.0]
__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