Source code for featuretools.primitives.standard.aggregation.all_primitive

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

from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
from featuretools.utils.gen_utils import Library, import_or_none

dd = import_or_none("dask.dataframe")

[docs]class All(AggregationPrimitive): """Calculates if all values are 'True' in a list. Description: Given a list of booleans, return `True` if all of the values are `True`. Examples: >>> all = All() >>> all([False, False, False, True]) False """ name = "all" input_types = [ [ColumnSchema(logical_type=Boolean)], [ColumnSchema(logical_type=BooleanNullable)], ] return_type = ColumnSchema(logical_type=Boolean) stack_on_self = False compatibility = [Library.PANDAS, Library.DASK] description_template = "whether all of {} are true" def get_function(self, agg_type=Library.PANDAS): if agg_type == Library.DASK: def chunk(s): return s.agg(np.all) def agg(s): return s.agg(np.all) return dd.Aggregation(, chunk=chunk, agg=agg) return np.all