Details
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Bug
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Status: Resolved
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Critical
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Resolution: Fixed
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None
Description
Calling to_pandas on a pyarrow.Array with a timezone aware timestamp type, removes the timezone in the resulting pandas.Series.
>>> import pyarrow as pa >>> a = pa.array([1], type=pa.timestamp('us', tz='America/Los_Angeles')) >>> a.to_pandas() 0 1970-01-01 00:00:00.000001 dtype: datetime64[ns]
Previous behavior from 0.14.1 of converting a pyarrow.Column to_pandas retained the timezone.
In [4]: import pyarrow as pa ...: a = pa.array([1], type=pa.timestamp('us', tz='America/Los_Angeles')) ...: c = pa.Column.from_array('ts', a) In [5]: c.to_pandas() Out[5]: 0 1969-12-31 16:00:00.000001-08:00 Name: ts, dtype: datetime64[ns, America/Los_Angeles]
Attachments
Issue Links
- relates to
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ARROW-6429 [CI][Crossbow] Nightly spark integration job fails
- Resolved
- links to