[jira] [Commented] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

["Matthew Rocklin (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16731491#comment-16731491 ] 

Matthew Rocklin commented on ARROW-1989:
----------------------------------------

I would find this fix useful.  

In particular I think that it might be useful to point users towards possible solutions, like the `allow_truncated_timestamps=True` option.

> [Python] Better UX on timestamp conversion to Pandas
> ----------------------------------------------------
>
>                 Key: ARROW-1989
>                 URL: https://issues.apache.org/jira/browse/ARROW-1989
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Uwe L. Korn
>            Priority: Major
>             Fix For: 0.13.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that they have dates that are larger than Pandas can represent with their nanosecond representation. Currently they simply see an Arrow exception and think that this problem is caused by Arrow. We should try to change the error from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX. This conversion is needed as Pandas does only support nanosecond timestamps. Your data is likely out of the range that can be represented with nanosecond resolution.
> {code}



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