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https://issues.apache.org/jira/browse/BEAM-12495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17363989#comment-17363989
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Brian Hulette commented on BEAM-12495:
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Sent https://github.com/apache/beam/pull/15019 which should detect this
situation and raise a helpful error (rather than returning the wrong result).
Unfortunately to actually fix this we will need to address the upstream bug:
https://github.com/pandas-dev/pandas/issues/36470
> DataFrame API: groupby(dropna=False) still drops NAs when grouping on
> multiple columns or indexes
> -------------------------------------------------------------------------------------------------
>
> Key: BEAM-12495
> URL: https://issues.apache.org/jira/browse/BEAM-12495
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Brian Hulette
> Priority: P2
> Labels: dataframe-api
> Time Spent: 1h
> Remaining Estimate: 0h
>
> {code}
> df.groupby(['foo', 'bar'], dropna=False).sum()
> {code}
> This will still drop NAs in the output.
> This is due to pandas bug
> [36470|https://github.com/pandas-dev/pandas/issues/36470] "BUG: groupby(...,
> dropna=False) excludes NA values when grouping on MultiIndex levels".
> We implement groupby by moving all grouped data into the index and requiring
> Index() partitioning, so we will always run into this issue, even when the
> user is grouping on columns, not indexes.
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