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https://issues.apache.org/jira/browse/ARROW-8066?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Markovtsev Vadim updated ARROW-8066:
------------------------------------
Description:
The original description is at
[https://github.com/pandas-dev/pandas/issues/32587]
was:
The original description is at
[https://github.com/pandas-dev/pandas/issues/32587]
|h4. Code Sample, a copy-pastable example if possible
import pandas as pd from datetime import datetime, timezone df =
pd.DataFrame.from_records([ (1, datetime.now().replace(tzinfo=timezone.utc)),
(2, datetime.now().replace(tzinfo=timezone.min))], columns=["1", "2"])
print(df["2"]) print() df.to_feather("/tmp/1") df2 = pd.read_feather("/tmp/1")
print(df2["2"])
This code will output: {{0 2020-03-10 18:13:49.405598+00:00
1 2020-03-10 18:13:49.405626-23:59
Name: 2, dtype: object
0 2020-03-10 18:13:49.405598
1 2020-03-10 18:13:49.405626
Name: 2, dtype: datetime64[ns]}}h4. Problem description
The round-trip dtype changed from the correct {{object}} to incorrect
{{datetime64}}. Thus the timezones were discarded in Arrow and the timestamps
became invalid.h4. Expected Output
(identical) {{0 2020-03-10 18:13:49.405598+00:00
1 2020-03-10 18:13:49.405626-23:59
Name: 2, dtype: object
0 2020-03-10 18:13:49.405598+00:00
1 2020-03-10 18:13:49.405626-23:59
Name: 2, dtype: object}}h4. Output of {{pd.show_versions()}}|
> PyArrow discards timezones
> --------------------------
>
> Key: ARROW-8066
> URL: https://issues.apache.org/jira/browse/ARROW-8066
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.16.0
> Reporter: Markovtsev Vadim
> Priority: Major
>
> The original description is at
> [https://github.com/pandas-dev/pandas/issues/32587]
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