Source code for featuretools.primitives.standard.transform.natural_language.num_unique_separators

import pandas as pd
from woodwork.column_schema import ColumnSchema
from woodwork.logical_types import IntegerNullable, NaturalLanguage

from featuretools.primitives.base import TransformPrimitive

NATURAL_LANGUAGE_SEPARATORS = [" ", ".", ",", "!", "?", ";", "\n"]

[docs]class NumUniqueSeparators(TransformPrimitive): r"""Calculates the number of unique separators. Description: Given a string and a list of separators, determine the number of unique separators in each string. If a string is null determined by pd.isnull return pd.NA. Args: separators (list, optional): a list of separator characters to count. ``[" ", ".", ",", "!", "?", ";", "\n"]`` is used by default. Examples: >>> x = ["First. Line.", "This. is the second, line!", "notinlist@#$%^%&"] >>> num_unique_separators = NumUniqueSeparators([".", ",", "!"]) >>> num_unique_separators(x).tolist() [1, 3, 0] """ name = "num_unique_separators" input_types = [ColumnSchema(logical_type=NaturalLanguage)] return_type = ColumnSchema(logical_type=IntegerNullable, semantic_tags={"numeric"})
[docs] def __init__(self, separators=NATURAL_LANGUAGE_SEPARATORS): assert separators is not None, "separators needs to be defined" self.separators = separators
def get_function(self): def count_unique_separator(s): if pd.isnull(s): return pd.NA return len(set(self.separators).intersection(set(s))) def get_separator_count(column): return column.apply(count_unique_separator) return get_separator_count