You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@beam.apache.org by "Brian Hulette (Jira)" <ji...@apache.org> on 2021/03/09 22:24:00 UTC

[jira] [Commented] (BEAM-11777) Support correct kwargs in aggregation methods on DataFrame, Series

    [ https://issues.apache.org/jira/browse/BEAM-11777?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17298400#comment-17298400 ] 

Brian Hulette commented on BEAM-11777:
--------------------------------------

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=).



--
This message was sent by Atlassian Jira
(v8.3.4#803005)