49 # for uniques in hashtables)
424     def _unique(self, const {{dtype}}_t[:] values, {{name}}Vector uniques,  argument
435         uniques : {{name}}Vector
436             Vector into which uniques will be written
438             Number of existing entries in uniques
447             Whether NA-values should be ignored for calculating the uniques. If
456             in the vector of uniques should be returned.
460         uniques : ndarray[{{dtype}}]
463             The labels from values to uniques
477         ud = uniques.data
522                             if uniques.external_view_exists:
524                                                  "uniques held, but "
526                             uniques.resize()
539             return uniques.to_array(), np.asarray(labels)
540         return uniques.to_array()
552             in the vector of uniques should be returned.
556         uniques : ndarray[{{dtype}}]
559             The labels from values to uniques
561         uniques = {{name}}Vector()
562         return self._unique(values, uniques, ignore_na=False,
570         Missing values are not included in the "uniques" for this method.
591         uniques : ndarray[{{dtype}}]
594             The labels from values to uniques
601     def get_labels(self, const {{dtype}}_t[:] values, {{name}}Vector uniques,  argument
604         _, labels = self._unique(values, uniques, count_prior=count_prior,
618             {{name}}Vector uniques = {{name}}Vector()
622         ud = uniques.data
645                             uniques.resize()
650         arr_uniques = uniques.to_array()
802     def _unique(self, ndarray[object] values, ObjectVector uniques,  argument
813         uniques : ObjectVector
814             Vector into which uniques will be written
816             Number of existing entries in uniques
825             Whether NA-values should be ignored for calculating the uniques. If
830             in the vector of uniques should be returned.
834         uniques : ndarray[object]
837             The labels from values to uniques
900         # uniques
902             uniques.append(values[uindexer[i]])
905             return uniques.to_array(), np.asarray(labels)
906         return uniques.to_array()
918             in the vector of uniques should be returned.
922         uniques : ndarray[object]
925             The labels from values to uniques
927         uniques = ObjectVector()
928         return self._unique(values, uniques, ignore_na=False,
936         Missing values are not included in the "uniques" for this method.
955         uniques : ndarray[object]
958             The labels from values to uniques
965     def get_labels(self, ndarray[object] values, ObjectVector uniques,  argument
968         _, labels = self._unique(values, uniques, count_prior=count_prior,
1067     def _unique(self, ndarray[object] values, ObjectVector uniques,  argument
1078         uniques : ObjectVector
1079             Vector into which uniques will be written
1081             Number of existing entries in uniques
1090             Whether NA-values should be ignored for calculating the uniques. If
1095             in the vector of uniques should be returned.
1099         uniques : ndarray[object]
1102             The labels from values to uniques
1136                 uniques.append(val)
1148             return uniques.to_array(), np.asarray(labels)
1149         return uniques.to_array()
1161             in the vector of uniques should be returned.
1165         uniques : ndarray[object]
1168             The labels from values to uniques
1170         uniques = ObjectVector()
1171         return self._unique(values, uniques, ignore_na=False,
1179         Missing values are not included in the "uniques" for this method.
1198         uniques : ndarray[object]
1201             The labels from values to uniques
1208     def get_labels(self, ndarray[object] values, ObjectVector uniques,  argument
1211         _, labels = self._unique(values, uniques, count_prior=count_prior,