featuretools.primitives.NumConsecutiveGreaterMean

class featuretools.primitives.NumConsecutiveGreaterMean(skipna=True)

Determines the length of the longest subsequence above the mean.

Description:

Given a list of numbers, find the longest subsequence of numbers larger than the mean of the entire sequence. Return the length of the longest subsequence.

Parameters:

skipna (bool) – If this is False and any value in x is NaN, then the result will be NaN. If True, NaN values are skipped. Default is True.

Examples

>>> num_consecutive_greater_mean = NumConsecutiveGreaterMean()
>>> num_consecutive_greater_mean([1, 2, 3, 4, 5, 6])
3.0

We can also control the way NaN values are handled.

>>> num_consecutive_greater_mean = NumConsecutiveGreaterMean(skipna=False)
>>> num_consecutive_greater_mean([1, 2, 3, 4, 5, 6, None])
nan

__init__(skipna=True)

Methods

__init__([skipna])
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
compatibility	Additional compatible libraries
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
series_library
stack_on
stack_on_exclude
stack_on_self
uses_calc_time