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Posted to jira@arrow.apache.org by "Joris Van den Bossche (Jira)" <ji...@apache.org> on 2020/12/16 08:45:00 UTC
[jira] [Closed] (ARROW-10935) [Python] pa.array() doesn't support
pa.lib.TimestampScalar objects
[ https://issues.apache.org/jira/browse/ARROW-10935?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joris Van den Bossche closed ARROW-10935.
-----------------------------------------
Resolution: Duplicate
> [Python] pa.array() doesn't support pa.lib.TimestampScalar objects
> ------------------------------------------------------------------
>
> Key: ARROW-10935
> URL: https://issues.apache.org/jira/browse/ARROW-10935
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 2.0.0
> Environment: Windows 10, Python 3.7.4, PyArrow 2.0.0
> Reporter: slatebit
> Priority: Blocker
>
> I encountered this edge case bug in PyArrow v2.0.0. For some reason, pa.array() does not know how to support pa.lib.TimestampScalar objects. This bug completely blocks my specific use case, although I do recognize that this edge case seems kind of wonky. Nonetheless, I don't see any reason why PyArrow would not understand one of it's own object types.
>
> Stacktrace:
> {code:java}
> ArrowInvalid: Could not convert 2020-11-04 22:50:16.276892 with type pyarrow.lib.TimestampScalar: did not recognize Python value type when inferring an Arrow data type
> {code}
>
> Reproducible Code:
> {code:java}
> import pandas as pd
> import pyarrow as pa
> pa.array([pa.scalar(pd.to_datetime('2020-11-04 22:50:16.276892000'))])
> {code}
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