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]

Methods

`__init__`()
`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
`uses_calc_time`
`uses_full_dataframe`

featuretools.primitives.CumSum

featuretools.primitives.CumMin