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https://issues.apache.org/jira/browse/BEAM-11777?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17298400#comment-17298400
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Brian Hulette commented on BEAM-11777:
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This may be incorrect, it looks like agg passes kwargs back down to the
underlying implementation, for example df.agg('count', level='Person') seems to
work, even though agg doesn't document a level= kwarg. To close this out lets
just make sure there are tests verifying the various arguments.
> Support correct kwargs in aggregation methods on DataFrame, Series
> ------------------------------------------------------------------
>
> Key: BEAM-11777
> URL: https://issues.apache.org/jira/browse/BEAM-11777
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Priority: P2
> Labels: dataframe-api
>
> {DataFrame,Series}.{all, any, max, min, prod, mean, median, sum} are all
> implemented via frame_base._agg_method, which just re-uses
> {DataFrame,Series}.agg}. However the pandas operations have some different
> kwargs that are not supported by agg. Some are universal (level=, skip_na=),
> others are unique to each operation (numeric_only= or bool_only=).
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