class OrdinalEncoderImpl():
def __init__(self, categories='auto', dtype=None):
self._hyperparams = {'categories': categories, 'dtype': dtype}
def fit(self, X, y=None):
self._sklearn_model = SKLModel(**self._hyperparams)
if (y is not None):
self._sklearn_model.fit(X, y)
else:
self._sklearn_model.fit(X)
return self
def transform(self, X):
return self._sklearn_model.transform(X)
class NanOrdinalEncoder(_BaseEncoder):
def __init__(self):
self.lbe = OrdinalEncoder()
def fit(self, X):
self.lbe.fit(X)
return self
def transform(self, X):
result = self.lbe.transform(X)
for col in range(result.shape[1]):
nan_idx = list(self.lbe.categories_[col]).index(nan_replace)
column = result[:, col]
column[column == nan_idx] = np.nan
return result