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

import numpy as np
from woodwork.column_schema import ColumnSchema
from woodwork.logical_types import Boolean, BooleanNullable

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

[docs]class And(TransformPrimitive): """Performs element-wise logical AND of two lists. Description: Given a list of booleans X and a list of booleans Y, determine whether each value in X is `True`, and whether its corresponding value in Y is also `True`. Examples: >>> _and = And() >>> _and([False, True, False], [True, True, False]).tolist() [False, True, False] """ name = "and" input_types = [ [ ColumnSchema(logical_type=BooleanNullable), ColumnSchema(logical_type=BooleanNullable), ], [ColumnSchema(logical_type=Boolean), ColumnSchema(logical_type=Boolean)], [ ColumnSchema(logical_type=Boolean), ColumnSchema(logical_type=BooleanNullable), ], [ ColumnSchema(logical_type=BooleanNullable), ColumnSchema(logical_type=Boolean), ], ] return_type = ColumnSchema(logical_type=BooleanNullable) commutative = True compatibility = [Library.PANDAS, Library.DASK, Library.SPARK] description_template = "whether {} and {} are true" def get_function(self): return np.logical_and def generate_name(self, base_feature_names): return "AND(%s, %s)" % (base_feature_names[0], base_feature_names[1])