MeanTransform

class MeanTransform(in_column: str, window: int, seasonality: int = 1, alpha: float = 1, min_periods: int = 1, fillna: float = 0, out_column: Optional[str] = None)

Bases: etna.transforms.math.statistics.WindowStatisticsTransform

MeanTransform computes average value for given window.

\[MeanTransform(x_t) = \sum_{i=1}^{window}{x_{t - i}\cdot\alpha^{i - 1}}\]

Init MeanTransform.

Parameters

• in_column (str) – name of processed column

• window (int) – size of window to aggregate

• seasonality (int) – seasonality of lags to compute window’s aggregation with

• alpha (float) – autoregressive coefficient

• min_periods (int) – min number of targets in window to compute aggregation; if there is less than min_periods number of targets return None

• fillna (float) – value to fill results NaNs with

• out_column (str, optional) – result column name. If not given use self.__repr__()

Inherited-members

Methods

fit(*args)	Fits transform.
fit_transform(df)	May be reimplemented.
inverse_transform(df)	Inverse transforms dataframe.
transform(df)	Compute feature's value.

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

Compute feature’s value.

Parameters

df (pd.DataFrame) – dataframe to generate features for

Returns

result – dataframe with results

Return type

pd.DataFrame