BUG: Interchange protocol implementation allows non-string column names

[MarcoGorelli]

• closes BUG: Interchange protocol implementation allows non-string column names #56701 (Replace xxxx with the GitHub issue number)
• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations to new arguments/methods/functions.
• Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature.

[MarcoGorelli]

not sure what this line was ever meant to achieve, as nothing is done with df2, it's just re-assigned to in L172

keeping it in results in

>           df.loc[null_idx, col] = None

pandas/tests/interchange/test_impl.py:172: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/core/indexing.py:[91](https://github.com/pandas-dev/pandas/actions/runs/7727513398/job/21066166133#step:8:93)2: in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
pandas/core/indexing.py:1[94](https://github.com/pandas-dev/pandas/actions/runs/7727513398/job/21066166133#step:8:96)6: in _setitem_with_indexer
    self._setitem_with_indexer_split_path(indexer, value, name)
pandas/core/indexing.py:2039: in _setitem_with_indexer_split_path
    self._setitem_single_column(loc, value, pi)
pandas/core/indexing.py:2170: in _setitem_single_column
    self.obj._mgr.column_setitem(loc, plane_indexer, value)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = BlockManager
Items: Index(['x', 'y', 'z'], dtype='object')
Axis 1: RangeIndex(start=0, stop=5, step=1)
NumpyBlock: slice(0, 3, 1), 3 x 5, dtype: float64
loc = 0, idx = array([2, 3, 1, 0]), value = None, inplace_only = False

    def column_setitem(
        self, loc: int, idx: int | slice | np.ndarray, value, inplace_only: bool = False
    ) -> None:
        """
        Set values ("setitem") into a single column (not setting the full column).
    
        This is a method on the BlockManager level, to avoid creating an
        intermediate Series at the DataFrame level (`s = df[loc]; s[idx] = value`)
        """
        needs_to_warn = False
        if warn_copy_on_write() and not self._has_no_reference(loc):
            if not isinstance(
                self.blocks[self.blknos[loc]].values,
                (ArrowExtensionArray, ArrowStringArray),
            ):
                # We might raise if we are in an expansion case, so defer
                # warning till we actually updated
                needs_to_warn = True
    
        elif using_copy_on_write() and not self._has_no_reference(loc):
            blkno = self.blknos[loc]
            # Split blocks to only copy the column we want to modify
            blk_loc = self.blklocs[loc]
            # Copy our values
            values = self.blocks[blkno].values
            if values.ndim == 1:
                values = values.copy()
            else:
                # Use [blk_loc] as indexer to keep ndim=2, this already results in a
                # copy
                values = values[[blk_loc]]
            self._iset_split_block(blkno, [blk_loc], values)
    
        # this manager is only created temporarily to mutate the values in place
        # so don't track references, otherwise the `setitem` would perform CoW again
        col_mgr = self.iget(loc, track_ref=False)
        if inplace_only:
            col_mgr.setitem_inplace(idx, value)
        else:
            new_mgr = col_mgr.setitem((idx,), value)
            self.iset(loc, new_mgr._block.values, inplace=True)
    
        if needs_to_warn:
>           warnings.warn(
                COW_WARNING_GENERAL_MSG,
                FutureWarning,
                stacklevel=find_stack_level(),
            )
E           FutureWarning: Setting a value on a view: behaviour will change in pandas 3.0.
E           You are mutating a Series or DataFrame object, and currently this mutation will
E           also have effect on other Series or DataFrame objects that share data with this
E           object. In pandas 3.0 (with Copy-on-Write), updating one Series or DataFrame object
E           will never modify another.

I think the simplest thing is to just remove it?

[mroeschke]

Looks good just a merge conflict

[WillAyd]

lgtm

[mroeschke]

Thanks @MarcoGorelli