LogTransform

class LogTransform(in_column: str, base: int = 10, inplace: bool = True, out_column: Optional[str] = None)

Bases: etna.transforms.base.Transform

LogTransform applies logarithm transformation for given series.

Init LogTransform.

Parameters

• in_column (str) – column to apply transform

• base (int) – base of logarithm to apply to series

• inplace (bool) –

  • if True, apply logarithm transformation inplace to in_column,

  • if False, add column 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 method does nothing and is kept for compatibility.
fit_transform(df)	May be reimplemented.
inverse_transform(df)	Apply inverse transformation to the dataset.
load(path)	Load an object.
save(path)	Save the object.
to_dict()	Collect all information about etna object in dict.
transform(df)	Apply log transformation to the dataset.

fit(df: pandas.core.frame.DataFrame) → etna.transforms.math.log.LogTransform

Fit method does nothing and is kept for compatibility.

Parameters

df (pandas.core.frame.DataFrame) – dataframe with data.

Returns

result

Return type

LogTransform

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

Apply inverse transformation to the dataset.

Parameters

df (pandas.core.frame.DataFrame) – dataframe with data to transform.

Returns

result – transformed series

Return type

pd.DataFrame

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

Apply log transformation to the dataset.

Parameters

df (pandas.core.frame.DataFrame) – dataframe with data to transform.

Returns

result – transformed dataframe

Return type

pd.Dataframe