Based on the GitHub issue description and traceback, I can analyze the problem directly. The issue is in `sklearn/utils/_set_output.py` in the `_wrap_in_pandas_container` function. Let me analyze the traceback:

1. The error occurs in `_wrap_in_pandas_container` at line 59: `data_to_wrap.index = index`
2. The problem is when a transformer returns a DataFrame with a different number of rows (aggregated data), the code tries to assign the original input's index to the output DataFrame
3. This fails because the number of elements don't match (4 elements in output vs 96 in original input)

Looking at the traceback and the hint in the issue:
- The code at lines 55-62 in `_set_output.py` checks if `data_to_wrap` is already a DataFrame
- If it is, and `index is not None`, it overwrites the DataFrame's index with the original input's index
- This breaks when the transformer aggregates data (changes row count)

The fix should be to NOT overwrite the index when the DataFrame already has an index that doesn't match the length of the new index. According to the hints:

> In principle, we can have a less restrictive requirement and only set the index if it is not defined.

The solution is to check if the lengths match before attempting to set the index, OR simply not set the index when the data is already a DataFrame (since it already has its own index from the transformer).

Here is the patch:

--- a/sklearn/utils/_set_output.py
+++ b/sklearn/utils/_set_output.py
@@ -55,7 +55,7 @@ def _wrap_in_pandas_container(
     if isinstance(data_to_wrap, pd.DataFrame):
         if columns is not None:
             data_to_wrap.columns = columns
-        if index is not None:
+        if index is not None and len(index) == len(data_to_wrap):
             data_to_wrap.index = index
         return data_to_wrap