Source code for featuretools.primitives.standard.transform.binary.less_than_equal_to

import numpy as np
import pandas as pd
import pandas.api.types as pdtypes
from woodwork.column_schema import ColumnSchema
from woodwork.logical_types import BooleanNullable, Datetime, Ordinal

from featuretools.primitives.base.transform_primitive_base import TransformPrimitive
from featuretools.utils.gen_utils import Library

[docs]class LessThanEqualTo(TransformPrimitive): """Determines if values in one list are less than or equal to another list. Description: Given a list of values X and a list of values Y, determine whether each value in X is less than or equal to each corresponding value in Y. Equal pairs will return `True`. Examples: >>> less_than_equal_to = LessThanEqualTo() >>> less_than_equal_to([2, 1, 2], [1, 2, 2]).tolist() [False, True, True] """ name = "less_than_equal_to" input_types = [ [ ColumnSchema(semantic_tags={"numeric"}), ColumnSchema(semantic_tags={"numeric"}), ], [ColumnSchema(logical_type=Datetime), ColumnSchema(logical_type=Datetime)], [ColumnSchema(logical_type=Ordinal), ColumnSchema(logical_type=Ordinal)], ] return_type = ColumnSchema(logical_type=BooleanNullable) compatibility = [Library.PANDAS, Library.DASK, Library.SPARK] description_template = "whether {} is less than or equal to {}" def get_function(self): def less_than_equal(val1, val2): val1_is_categorical = pdtypes.is_categorical_dtype(val1) val2_is_categorical = pdtypes.is_categorical_dtype(val2) if val1_is_categorical and val2_is_categorical: if not all( == return val1.where(pd.isnull, np.nan) elif val1_is_categorical or val2_is_categorical: # This can happen because CFM does not set proper dtypes for intermediate # features, so some agg features that should be Ordinal don't yet have correct type. return val1.where(pd.isnull, np.nan) return val1 <= val2 return less_than_equal def generate_name(self, base_feature_names): return "%s <= %s" % (base_feature_names[0], base_feature_names[1])