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https://issues.apache.org/jira/browse/ARROW-3448?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17393197#comment-17393197
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Joris Van den Bossche commented on ARROW-3448:
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I don't think this is actually fixed. When converting back the nested list with
timestamp columns, we create numpy arrays with datetime64 dtype, not object
dtype arrays with datetime objects:
{code}
>>> df = pd.DataFrame({'a': datetime_data})
>>> table = pa.table(df)
>>> table
pyarrow.Table
a: list<item: timestamp[us]>
child 0, item: timestamp[us]
>>> table.to_pandas()['a'][0]
array(['2015-01-05T12:00:00.000000', '2020-08-22T10:05:00.000000'],
dtype='datetime64[us]')
>>> df['a'][0]
[datetime.datetime(2015, 1, 5, 12, 0), datetime.datetime(2020, 8, 22, 10, 5)]
{code}
But as I mentioned above, not sure we actually *want* to change this behaviour.
> [Python] Pandas roundtrip doesn't preserve list of datetime objects
> -------------------------------------------------------------------
>
> Key: ARROW-3448
> URL: https://issues.apache.org/jira/browse/ARROW-3448
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: Krisztian Szucs
> Priority: Major
> Labels: pull-request-available
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Adding the following to the pandas_example.py::dataframe_with_lists functionn:
> {code:python}
> datetime_data = [
> [datetime(2015, 1, 5, 12, 0, 0), datetime(2020, 8, 22, 10, 5, 0)],
> [datetime(2024, 5, 5, 5, 49, 1), datetime(2015, 12, 24, 22, 10, 17)],
> [datetime(1996, 4, 30, 2, 38, 11)],
> None,
> [datetime(1987, 1, 27, 8, 21, 59)]
> ]
> type = pa.timestamp('s'|'ms'|'us'|'ns')
> {code}
> breaks the tests cases, because the roundtrip doesn't preserve the object
> type.
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