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

Methods

`__init__`([skipna])
`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`	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
`stack_on`
`stack_on_exclude`
`stack_on_self`
`uses_calc_time`

featuretools.primitives.Count

featuretools.primitives.Sum