ResampleWithDistributionTransform

class ResampleWithDistributionTransform(in_column: str, distribution_column: str, inplace: bool = True, out_column: Optional[str] = None)

Bases: etna.transforms.base.PerSegmentWrapper

ResampleWithDistributionTransform resamples the given column using the distribution of the other column.

Warning

This transform can suffer from look-ahead bias. For transforming data at some timestamp it uses information from the whole train part.

Init ResampleWithDistributionTransform.

Parameters

• in_column (str) – name of column to be resampled

• distribution_column (str) – name of column to obtain the distribution from

• inplace (bool) –

  • if True, apply resampling inplace to in_column,

  • if False, add transformed column to dataset

• out_column (Optional[str]) – name of added column. If not given, use self.__repr__()

Inherited-members

Methods

fit(df)	Fit transform on each segment.
fit_transform(df)	May be reimplemented.
inverse_transform(df)	Apply inverse_transform to each segment.
transform(df)	Apply transform to each segment separately.