_OneSegmentTimeSeriesImputerTransform

class _OneSegmentTimeSeriesImputerTransform(in_column: str, strategy: str, window: int, seasonality: int, default_value: Optional[float], constant_value: float = 0)

Bases: etna.transforms.base.Transform

One segment version of transform to fill NaNs in series of a given dataframe.

• It is assumed that given series begins with first non NaN value.

• This transform can’t fill NaNs in the future, only on train data.

• This transform can’t fill NaNs if all values are NaNs. In this case exception is raised.

Create instance of _OneSegmentTimeSeriesImputerTransform.

Parameters

• in_column (str) – name of processed column

• strategy (str) –

  filling value in missing timestamps:

  • If “zero”, then replace missing dates with zeros

  • If “mean”, then replace missing dates using the mean in fit stage.

  • If “running_mean” then replace missing dates using mean of subset of data

  • If “forward_fill” then replace missing dates using last existing value

  • If “seasonal” then replace missing dates using seasonal moving average

  • If “constant” then replace missing dates using constant value.

• window (int) –

  In case of moving average and seasonality.

  • If window=-1 all previous dates are taken in account

  • Otherwise only window previous dates

• seasonality (int) – the length of the seasonality

• default_value (Optional[float]) – value which will be used to impute the NaNs left after applying the imputer with the chosen strategy

• constant_value (float) – value to fill gaps in “constant” strategy

Raises

ValueError: – if incorrect strategy given

Inherited-members

Methods

fit(df)	Fit preprocess params.
fit_transform(df)	May be reimplemented.
inverse_transform(df)	Inverse transform dataframe.
load(path)	Load an object.
save(path)	Save the object.
to_dict()	Collect all information about etna object in dict.
transform(df)	Transform given series.

fit(df: pandas.core.frame.DataFrame) → etna.transforms.missing_values.imputation._OneSegmentTimeSeriesImputerTransform

Fit preprocess params.

Parameters

df (pd.DataFrame) – dataframe with series to fit preprocess params with

Returns

self – fitted preprocess

Return type

_OneSegmentTimeSeriesImputerTransform

inverse_transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

Inverse transform dataframe.

Parameters

df (pd.Dataframe) – inverse transform in_column series of given dataframe

Returns

result – dataframe with in_column series with initial values

Return type

pd.DataFrame

transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

Transform given series.

Parameters

df (pd.Dataframe) – transform in_column series of given dataframe

Returns

result – dataframe with in_column series with filled gaps

Return type

pd.DataFrame