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`

featuretools.primitives.Count featuretools.primitives.Sum