da3630c4eccc04079e465256786f65d6d87e7b1f,pdpipe/sklearn_stages.py,Encode,__init__,#Encode#Any#Any#Any#,75

Before Change

        if columns is None:
            self._columns = None
        else:
            self._columns = _interpret_columns_param(columns)
        if exclude_columns is None:
            self._exclude_columns = []
        else:
            self._exclude_columns = _interpret_columns_param(exclude_columns)
        self._drop = drop
        self.encoders = {}
        col_str = _list_str(self._columns)
        super_kwargs = {
            "exmsg": Encode._DEF_ENCODE_EXC_MSG.format(col_str),
            "appmsg": Encode._DEF_ENCODE_APP_MSG.format(col_str),
            "desc": "Encode {}".format(col_str or "all categorical columns"),
        }
        super_kwargs.update(**kwargs)
        super().__init__(**super_kwargs)

    def _prec(self, df):

After Change

    ):
        self._drop = drop
        self.encoders = {}
        super_kwargs = {
            "columns": columns,
            "exclude_columns": exclude_columns,
            "desc_temp": "Encode {}",
        }
        super_kwargs.update(**kwargs)
        super_kwargs["none_columns"] = OfDtypes(["object", "category"])
        super().__init__(**super_kwargs)

    def _transformation(self, df, verbose, fit):
        raise NotImplementedError

Instances