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.Mean

class featuretools.primitives.Mean(skipna=True)[source]

Computes the average for a list of values.

Parameters

skipna (bool) – Determines if to use NA/null values. Defaults to True to skip NA/null.

Examples

>>> mean = Mean()
>>> mean([1, 2, 3, 4, 5, None])
3.0

We can also control the way NaN values are handled.

>>> mean = Mean(skipna=False)
>>> mean([1, 2, 3, 4, 5, None])
nan
__init__(skipna=True)[source]

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

Methods

__init__([skipna])

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([agg_type])

Attributes

base_of

base_of_exclude

commutative

compatibility

default_value

description_template

input_types

max_stack_depth

name

number_output_features

stack_on

stack_on_exclude

stack_on_self

uses_calc_time