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https://issues.apache.org/jira/browse/BEAM-11777?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17315077#comment-17315077
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Brian Hulette commented on BEAM-11777:
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Note the default values for numeric_only= and bool_only= (None) produce
non-deferred column values - it attempts to to convert each column and just
removes the ones that fail. We can't do this in our implementation.
We should probably disallow numeric_only=None, and choose defaults that are
consistent with the groupby aggregation functions.
> 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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