NOTICE

The upcoming release of Featuretools 1.0.0 contains several breaking changes. Users are encouraged to test this version prior to release by installing from GitHub:

pip install https://github.com/alteryx/featuretools/archive/woodwork-integration.zip

For details on migrating to the new version, refer to Transitioning to Featuretools Version 1.0. Please report any issues in the Featuretools GitHub repo or by messaging in Alteryx Open Source Slack.


featuretools.primitives.CumMean

class featuretools.primitives.CumMean[source]

Calculates the cumulative mean.

Description:

Given a list of values, return the cumulative mean (or running mean). There is no set window, so the mean at each point is calculated over all prior values. NaN values will return NaN, but in the window of a cumulative caluclation, they’re treated as 0.

Examples

>>> cum_mean = CumMean()
>>> cum_mean([1, 2, 3, 4, None, 5]).tolist()
[1.0, 1.5, 2.0, 2.5, nan, 2.5]
__init__()

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__()

Initialize self.

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

default_value

description_template

input_types

max_stack_depth

name

number_output_features

return_type

uses_calc_time

uses_full_dataframe