def __init__(
self, columns=None, exclude_columns=None, drop=True, **kwargs
):
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 __init__(self, scaler, columns=None, exclude_columns=None, **kwargs):
self.scaler = scaler
self._kwargs = kwargs
super_kwargs = {
'columns': columns,
'exclude_columns': exclude_columns,
'desc_temp': "Scale columns {}",
}
valid_super_kwargs = super()._init_kwargs()
for key in kwargs:
if key in valid_super_kwargs:
super_kwargs[key] = kwargs[key]
super_kwargs['none_columns'] = OfDtypes([np.number])
super().__init__(**super_kwargs)
def __init__(self,
columns=None,
exclude_columns=None,
drop=False,
non_neg=False,
const_shift=None,
**kwargs):
self._drop = drop
self._non_neg = non_neg
self._const_shift = const_shift
self._col_to_minval = {}
super_kwargs = {
'columns': columns,
'exclude_columns': exclude_columns,
'desc_temp': "Log-transform {}",
}
super_kwargs.update(**kwargs)
super_kwargs['none_columns'] = OfDtypes([np.number])
super().__init__(**super_kwargs)
def __init__(self,
columns=None,
dummy_na=False,
exclude_columns=None,
drop_first=True,
drop=True,
**kwargs):
self._dummy_na = dummy_na
self._drop_first = drop_first
self._drop = drop
self._dummy_col_map = {}
self._encoder_map = {}
super_kwargs = {
'columns': columns,
'exclude_columns': exclude_columns,
'desc_temp': "One-hot encode {}",
}
super_kwargs.update(**kwargs)
super_kwargs['none_columns'] = OfDtypes(['object', 'category'])
super().__init__(**super_kwargs)