dosubot[bot] commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5469545852

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   Hi @Archita-kale! I'm [Dosu](https://go.dosu.dev/dosubot) and I'm helping 
the Apache Superset team.
   
   I can't approve PR assignments myself, but from a technical standpoint the 
follow-up @kokhlo described is real and self-contained enough to tackle 
independently. Here's a quick summary of what's going on and what the fix would 
look like:
   
   In `pivot()`, NULL values in `columns` are already filled with `NULL_STRING` 
before the pivot 
[[1]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/utils/pandas_postprocessing/pivot.py#L73-L74),
 but `index` columns get no equivalent treatment. The call to 
`df.pivot_table(...)` passes `drop_missing_columns` as the `dropna` argument 
[[2]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/utils/pandas_postprocessing/pivot.py#L92-L101),
 and pandas' `dropna` on `pivot_table` only governs all-NaN *columns* — it does 
not preserve NULL keys in the index. So a NULL group that survives the 
`aggregate` step (per this PR's fix) is still silently dropped once it hits 
`pivot`.
   
   The natural fix mirrors what's already done for `columns` on [line 
74](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/utils/pandas_postprocessing/pivot.py#L73-L74):
 fill NULL values in the `index` columns (e.g., with `NULL_STRING`) before 
calling `pivot_table`. You'd then add a regression test analogous to the 
boxplot/histogram ones in #43682 — run `aggregate` → `pivot` with a NULL 
grouping value and assert the row is preserved. That would close item 1 of 
#43547 fully for the table/pivot-table visuals @kokhlo flagged as still 
affected.
   
   Since this touches a separate file (`pivot.py`) and is a distinct fix, 
submitting it as its own follow-up PR referencing #43547 and this discussion 
makes sense.
   
   Want me to look deeper into how `NULL_STRING` / 
`_restore_dropped_metric_columns` handle nulls elsewhere in the post-processing 
pipeline so you have a consistent pattern to follow for the index fill?
   
   
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