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Posted to notifications@superset.apache.org by "yiheng-kkk (via GitHub)" <gi...@apache.org> on 2026/08/29 08:50:15 UTC
[PR] fix(pandas-postprocessing): preserve null grouping values [superset]
yiheng-kkk opened a new pull request, #43682:
URL: https://github.com/apache/superset/pull/43682
### SUMMARY
Addresses item 1 of #43547.
Pandas drops null grouping keys by default, so grouped Histogram and Box Plot post-processing silently omitted those categories. This passes `dropna=False` in the shared aggregate path and the grouped Histogram path, with deterministic regressions for both behaviors.
This PR is intentionally limited to the missing-group issue. It does not address the separate frontend `NULL_STRING` label and tooltip inconsistencies reported in items 2 and 3.
AI assistance disclosure: OpenAI Codex assisted with repository and competition auditing, implementation, test preparation, and validation. The change was independently reviewed and validated against the repository's locked Python dependencies.
### BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF
Not applicable; the change is limited to backend DataFrame post-processing and is covered by deterministic output assertions.
### TESTING INSTRUCTIONS
- `.venv/bin/pytest -q tests/unit_tests/pandas_postprocessing/test_aggregate.py tests/unit_tests/pandas_postprocessing/test_histogram.py tests/unit_tests/pandas_postprocessing/test_boxplot.py` (25 passed)
- `.venv/bin/pytest -q tests/unit_tests/pandas_postprocessing` (142 passed)
- `PATH="$PWD/.venv/bin:$PATH" .venv/bin/pre-commit run` (all applicable staged hooks passed)
### ADDITIONAL INFORMATION
- [x] Has associated issue: #43547 (item 1 only)
- [ ] Required feature flags:
- [ ] Changes UI
- [ ] Includes DB Migration (follow approval process in [SIP-59](https://github.com/apache/superset/issues/13351))
- [ ] Migration is atomic, supports rollback & is backwards-compatible
- [ ] Confirm DB migration upgrade and downgrade tested
- [ ] Runtime estimates and downtime expectations provided
- [ ] Introduces new feature or API
- [ ] Removes existing feature or API
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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "kokhlo (via GitHub)" <gi...@apache.org>.
kokhlo commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5468028633
Verified the aggregate/histogram paths and the updated boxplot expectations — consistent with the fixture (the NULL region row now forms its own group, 4→5). One follow-up worth noting for the same post-processing pipeline:
pivot (superset/utils/pandas_postprocessing/pivot.py:325) calls df.pivot_table(...) with dropna=drop_missing_columns, which only governs all-NaN columns. NULL keys in the index are still dropped by pivot_table, so a query whose post-processing is aggregate → pivot will now keep the NULL group in the aggregate output but silently lose the same rows again at the pivot step. Charts that pivot (most table/pivot-table visuals) will not see the fix; only the direct aggregate/histogram/boxplot paths do.
Not a blocker for this PR — the dropna=False fix is correct where it is applied — but the sibling path probably wants the same treatment (pivot_table has no direct index-dropna flag; the usual approach is filling NULL index keys before the pivot, the way the codebase already handles NULL preservation structurally in _restore_dropped_metric_columns). Happy to take that follow-up separately if maintainers want it.
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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "kokhlo (via GitHub)" <gi...@apache.org>.
kokhlo commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5470986527
Please go ahead — the gap is yours.
One pointer from digging into it while reviewing this PR: `pivot_table` has no index-side dropna flag, so the usual approach is filling NULL index keys before the pivot (the way `_restore_dropped_metric_columns` already handles NULL preservation structurally), and the regression test should assert the NULL group survives the full aggregate → pivot chain, not just aggregate alone. Happy to review when the PR is up.
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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "dosubot[bot] (via GitHub)" <gi...@apache.org>.
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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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "Archita-kale (via GitHub)" <gi...@apache.org>.
Archita-kale commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5469540247
Hi @dosu, I noticed the follow-up mentioned regarding the aggregate → pivot post-processing path and the NULL index keys being dropped by pivot_table.
I’d love to work on this as a follow-up to #43682, including adding a regression test to ensure NULL grouping values are preserved through the pivot path.
Would it be okay for me to take this up and submit a PR?
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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "codecov[bot] (via GitHub)" <gi...@apache.org>.
codecov[bot] commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5461461764
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```diff
@@ Coverage Diff @@
## master #43682 +/- ##
===========================================
- Coverage 79.22% 57.47% -21.75%
===========================================
Files 2879 2879
Lines 166087 166087
Branches 38420 38420
===========================================
- Hits 131581 95465 -36116
- Misses 32023 69726 +37703
+ Partials 2483 896 -1587
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Re: [PR] fix(pandas-postprocessing): preserve null grouping values [superset]
Posted by "bito-code-review[bot] (via GitHub)" <gi...@apache.org>.
bito-code-review[bot] commented on PR #43682:
URL: https://github.com/apache/superset/pull/43682#issuecomment-5461392797
AI Code Review is in progress (usually takes 3 to 15 minutes unless it's a very large PR).
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