featuretools.primitives.CumMean#

class featuretools.primitives.CumMean[source]#

计算累积平均值.

Description:: 给定一个数值列表,返回累积平均值（或运行平均值）. 没有设定窗口大小,因此每个点的平均值是基于所有先前值计算的. NaN 值将返回 NaN,但在累积计算的窗口中,它们被视为 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__`()
`flatten_nested_input_types`(input_types)	将嵌套的列模式输入展平成一个列表.
`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`
`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`
`uses_full_dataframe`