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https://issues.apache.org/jira/browse/SPARK-23314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16356189#comment-16356189
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Apache Spark commented on SPARK-23314:
--------------------------------------

User 'icexelloss' has created a pull request for this issue:
https://github.com/apache/spark/pull/20537

> Pandas grouped udf on dataset with timestamp column error 
> ----------------------------------------------------------
>
>                 Key: SPARK-23314
>                 URL: https://issues.apache.org/jira/browse/SPARK-23314
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 2.3.0
>            Reporter: Felix Cheung
>            Priority: Major
>
> Under  SPARK-22216
> When testing pandas_udf on group bys, I saw this error with the timestamp 
> column.
> File "pandas/_libs/tslib.pyx", line 3593, in 
> pandas._libs.tslib.tz_localize_to_utc
> AmbiguousTimeError: Cannot infer dst time from Timestamp('2015-11-01 
> 01:29:30'), try using the 'ambiguous' argument
> For details, see Comment box. I'm able to reproduce this on the latest 
> branch-2.3 (last change from Feb 1 UTC)



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