Noticed while working on #17644 that `diff` and `fillna` were make some unnecessary shallow copies of the `grouping.value` object. Also noticed that `_cov_or_corr` just pulled the column names out of `grouping.value` object, so made a separate API, `values_column_names` to just create the column names without pulling out the actual columns.

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - Bradley Dice (https://github.com/bdice)

URL: #17646

Follow up to #17644

This PR changes `MultiIndex` to delay computing `self._level` and `self._codes` via factorization of `self._column` until needed by certain methods. Before, for state consistency, those attributes were always eagerly computed. As discussed offline the performance benefit of not eagerly computing those attributes is more desirable.

```python
import cudf
df_train = cudf.datasets.randomdata(nrows=50_000_000, dtypes={"label": int, "weekday": int, "cat_2": int, "brand": int})
target = "label"
col = ['weekday', 'cat_2', 'brand']
df_gb= df_train[col + [target]].groupby(col)
%%time
df_gb.agg(['mean', 'count'])


# PR
CPU times: user 144 ms, sys: 23.9 ms, total: 168 ms
Wall time: 166 ms

  _     ._   __/__   _ _  _  _ _/_   Recorded: 12:12:46  Samples:  4
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.159     CPU time: 0.160
/   _/                      v5.0.0

Cell [3]

0.158 <module>  <ipython-input-3-ee51998a643a>:1
`- 0.158 wrapper  cudf/utils/performance_tracking.py:30
   `- 0.158 DataFrameGroupBy.agg  cudf/core/groupby/groupby.py:879
      |- 0.129 DataFrameGroupBy._aggregate  cudf/core/groupby/groupby.py:789
      `- 0.029 NumericalColumn.astype  cudf/core/column/column.py:1126
         `- 0.029 NumericalColumn.as_numerical_column  cudf/core/column/numerical.py:428
            `- 0.029 inner  contextlib.py:78
               `- 0.029 cast  cudf/core/_internals/unary.py:40


# branch 25.02 head
CPU times: user 369 ms, sys: 105 ms, total: 474 ms
Wall time: 478 ms


  _     ._   __/__   _ _  _  _ _/_   Recorded: 12:11:20  Samples:  79
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.480     CPU time: 0.478
/   _/                      v5.0.0

Cell [3]

0.479 <module>  <ipython-input-3-ee51998a643a>:1
`- 0.478 wrapper  cudf/utils/performance_tracking.py:30
   `- 0.478 DataFrameGroupBy.agg  cudf/core/groupby/groupby.py:879
      |- 0.267 cached_property.__get__  functools.py:979
      |  `- 0.267 _Grouping.keys  cudf/core/groupby/groupby.py:3534
      |     `- 0.267 wrapper  cudf/utils/performance_tracking.py:30
      |        `- 0.267 MultiIndex._from_data  cudf/core/multiindex.py:344
      |           `- 0.265 _compute_levels_and_codes  cudf/core/multiindex.py:67
      |              |- 0.230 factorize  cudf/core/algorithms.py:22
      |              |  |- 0.168 NumericalColumn._label_encoding  cudf/core/column/column.py:1516
      |              |  |  |- 0.097 [self]  cudf/core/column/column.py
      |              |  |  |- 0.031 as_column  cudf/core/column/column.py:1948
      |              |  |  |  `- 0.028 NumericalColumn.astype  cudf/core/column/column.py:1126
      |              |  |  |     `- 0.028 NumericalColumn.as_numerical_column  cudf/core/column/numerical.py:428
      |              |  |  |        `- 0.028 inner  contextlib.py:78
      |              |  |  |           `- 0.028 cast  cudf/core/_internals/unary.py:40
      |              |  |  |- 0.030 inner  contextlib.py:78
      |              |  |  |  `- 0.030 sort_by_key  cudf/core/_internals/sorting.py:160
      |              |  |  `- 0.007 NumericalColumn.take  cudf/core/column/column.py:943
      |              |  |     `- 0.007 inner  contextlib.py:78
      |              |  |        `- 0.007 gather  cudf/core/_internals/copying.py:18
      |              |  |- 0.051 NumericalColumn.unique  cudf/core/column/column.py:1342
      |              |  |  |- 0.036 inner  contextlib.py:78
      |              |  |  |  `- 0.036 drop_duplicates  cudf/core/_internals/stream_compaction.py:82
      |              |  |  `- 0.015 NumericalColumn.is_unique  cudf/core/column/column.py:1056
      |              |  |     `- 0.015 NumericalColumn.distinct_count  cudf/core/column/column.py:1108
      |              |  `- 0.006 NumericalColumn.dropna  cudf/core/column/column.py:294
      |              |     `- 0.006 NumericalColumn.copy  cudf/core/column/column.py:481
      |              `- 0.028 _compile_module_with_cache  cupy/cuda/compiler.py:473
      |                    [4 frames hidden]  cupy, <built-in>
      |- 0.133 DataFrameGroupBy._aggregate  cudf/core/groupby/groupby.py:789
      `- 0.079 wrapper  cudf/utils/performance_tracking.py:30
         `- 0.079 MultiIndex._from_columns_like_self  cudf/core/frame.py:194
            `- 0.079 wrapper  cudf/utils/performance_tracking.py:30
               |- 0.040 MultiIndex._copy_type_metadata  cudf/core/multiindex.py:2101
               |  `- 0.038 _compute_levels_and_codes  cudf/core/multiindex.py:67
               |     `- 0.038 factorize  cudf/core/algorithms.py:22
               |        |- 0.021 NumericalColumn._label_encoding  cudf/core/column/column.py:1516
               |        |  |- 0.010 [self]  cudf/core/column/column.py
               |        |  `- 0.007 inner  contextlib.py:78
               |        |     `- 0.007 sort_by_key  cudf/core/_internals/sorting.py:160
               |        `- 0.011 NumericalColumn.unique  cudf/core/column/column.py:1342
               |           `- 0.010 inner  contextlib.py:78
               |              `- 0.010 drop_duplicates  cudf/core/_internals/stream_compaction.py:82
               `- 0.039 MultiIndex._from_data  cudf/core/multiindex.py:344
                  `- 0.038 _compute_levels_and_codes  cudf/core/multiindex.py:67
                     `- 0.038 factorize  cudf/core/algorithms.py:22
                        |- 0.021 NumericalColumn._label_encoding  cudf/core/column/column.py:1516
                        |  |- 0.010 [self]  cudf/core/column/column.py
                        |  `- 0.007 inner  contextlib.py:78
                        |     `- 0.007 sort_by_key  cudf/core/_internals/sorting.py:160
                        `- 0.010 NumericalColumn.unique  cudf/core/column/column.py:1342
                           `- 0.010 inner  contextlib.py:78
                              `- 0.010 drop_duplicates  cudf/core/_internals/stream_compaction.py:82
```

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)
  - Matthew Murray (https://github.com/Matt711)

Approvers:
  - Vyas Ramasubramani (https://github.com/vyasr)

URL: #17728