| 372 | return new_values, new_mask |
| 373 | |
| 374 | def get_new_columns(self, value_columns: Index | None): |
| 375 | if value_columns is None: |
| 376 | if not self.has_nan: |
| 377 | return self.removed_level._rename(name=self.removed_name) |
| 378 | |
| 379 | lev = self.removed_level.insert(0, item=self.removed_level._na_value) |
| 380 | return lev.rename(self.removed_name) |
| 381 | |
| 382 | stride = len(self.removed_level) + self.has_nan |
| 383 | width = len(value_columns) |
| 384 | propagator = np.repeat(np.arange(width), stride) |
| 385 | |
| 386 | new_levels: FrozenList | list[Index] |
| 387 | |
| 388 | if isinstance(value_columns, MultiIndex): |
| 389 | new_levels = value_columns.levels + (self.removed_level_full,) # pyright: ignore[reportOperatorIssue] # noqa: RUF005 |
| 390 | new_names = value_columns.names + (self.removed_name,) # noqa: RUF005 |
| 391 | |
| 392 | new_codes = [lab.take(propagator) for lab in value_columns.codes] |
| 393 | else: |
| 394 | new_levels = [ |
| 395 | value_columns, |
| 396 | self.removed_level_full, |
| 397 | ] |
| 398 | new_names = [value_columns.name, self.removed_name] |
| 399 | new_codes = [propagator] |
| 400 | |
| 401 | repeater = self._repeater |
| 402 | |
| 403 | # The entire level is then just a repetition of the single chunk: |
| 404 | new_codes.append(np.tile(repeater, width)) |
| 405 | return MultiIndex( |
| 406 | levels=new_levels, codes=new_codes, names=new_names, verify_integrity=False |
| 407 | ) |
| 408 | |
| 409 | @cache_readonly |
| 410 | def _repeater(self) -> np.ndarray: |