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https://issues.apache.org/jira/browse/BEAM-12495?focusedWorklogId=611613&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-611613
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ASF GitHub Bot logged work on BEAM-12495:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 15/Jun/21 21:35
Start Date: 15/Jun/21 21:35
Worklog Time Spent: 10m
Work Description: codecov[bot] edited a comment on pull request #15019:
URL: https://github.com/apache/beam/pull/15019#issuecomment-861824969
#
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```diff
@@ Coverage Diff @@
## master #15019 +/- ##
==========================================
+ Coverage 83.74% 83.76% +0.02%
==========================================
Files 439 439
Lines 59041 59043 +2
==========================================
+ Hits 49442 49457 +15
+ Misses 9599 9586 -13
```
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------
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Issue Time Tracking
-------------------
Worklog Id: (was: 611613)
Time Spent: 50m (was: 40m)
> 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: 50m
> 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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