OneHotEncoderTransform¶

class OneHotEncoderTransform(in_column: str, out_column: Optional[str] = None)[source]¶

Encode categorical feature as a one-hot numeric features.

If unknown category is encountered during transform, the resulting one-hot encoded columns for this feature will be all zeros.

Init OneHotEncoderTransform.

Parameters

in_column (str) – Name of column to be encoded
out_column (Optional[str]) – Prefix of names of added columns. If not given, use self.__repr__()

Inherited-members

Methods

`fit`(df)	Fit One Hot encoder.
`fit_transform`(df)	May be reimplemented.
`inverse_transform`(df)	Inverse transforms dataframe.
`transform`(df)	Encode the in_column by fitted One Hot encoder.

Fit One Hot encoder.

Parameters: df (pandas.core.frame.DataFrame) – Dataframe with data to fit the transform
Returns: Fitted transform
Return type: etna.transforms.encoders.categorical.OneHotEncoderTransform

transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]¶

Encode the in_column by fitted One Hot encoder.

Parameters: df (pandas.core.frame.DataFrame) – Dataframe with data to transform
Returns: Dataframe with column with encoded values
Return type: pandas.core.frame.DataFrame