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PreviousImputer

Imputes missing values by using the most recent value.

Examples

from river import preprocessing

imputer = preprocessing.PreviousImputer()

imputer = imputer.learn_one({'x': 1, 'y': 2})
imputer.transform_one({'y': None})

{'y': 2}


imputer.transform_one({'x': None})

{'x': 1}

Methods

learn_one

Update with a set of features x.

A lot of transformers don't actually have to do anything during the learn_one step because they are stateless. For this reason the default behavior of this function is to do nothing. Transformers that however do something during the learn_one can override this method.

Parameters

  • x — 'dict'

Returns

Transformer: self

transform_one

Transform a set of features x.

Parameters

  • x — 'dict'

Returns

dict: The transformed values.