LagTransform¶
- class LagTransform(in_column: str, lags: Union[List[int], int], out_column: Optional[str] = None)[source]¶
Bases:
etna.transforms.base.Transform,etna.transforms.base.FutureMixinGenerates series of lags from given dataframe.
Create instance of LagTransform.
- Parameters
in_column (str) – name of processed column
lags (Union[List[int], int]) – int value or list of values for lags computation; if int, generate range of lags from 1 to given value
out_column (Optional[str]) –
base for the name of created columns;
if set the final name is ‘{out_column}_{lag_number}’;
if don’t set, name will be
transform.__repr__(), repr will be made for transform that creates exactly this column
- Raises
ValueError: – if lags value contains non-positive values
- Inherited-members
Methods
fit(df)Fit method does nothing and is kept for compatibility.
fit_transform(df)May be reimplemented.
inverse_transform(df)Inverse transforms dataframe.
load(path)Load an object.
save(path)Save the object.
to_dict()Collect all information about etna object in dict.
transform(df)Add lags to the dataset.
- fit(df: pandas.core.frame.DataFrame) etna.transforms.math.lags.LagTransform[source]¶
Fit method does nothing and is kept for compatibility.
- Parameters
df (pandas.core.frame.DataFrame) – dataframe with data.
- Returns
result
- Return type