featuretools.primitives.IsWorkingHours

class featuretools.primitives.IsWorkingHours(start_hour=8, end_hour=18)

Determines if a datetime falls during working hours on a 24-hour clock. Can configure start_hour and end_hour.

Parameters:

• start_hour (int) – Start hour of workday. Must adhere to 24-hour clock. Default is 8 (8am).

• end_hour (int) – End hour of workday. Must adhere to 24-hour clock. Default is 18 (6pm).

Examples

>>> import numpy as np
>>> from datetime import datetime
>>> dates = [datetime(2022, 6, 21, 16, 3, 3),
...          datetime(2019, 1, 3, 4, 4, 4),
...          datetime(2022, 1, 1, 12, 1, 2),
...          np.nan]
>>> is_working_hour = IsWorkingHours()
>>> is_working_hour(dates).tolist()
[True, False, True, False]
>>> is_working_hour = IsWorkingHours(15, 17)
>>> is_working_hour(dates).tolist()
[True, False, False, False]

__init__(start_hour=8, end_hour=18)

Methods

__init__([start_hour, end_hour])
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
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
stack_on
stack_on_exclude
stack_on_self
uses_calc_time
uses_full_dataframe