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Posted to issues@arrow.apache.org by "Joris Van den Bossche (Jira)" <ji...@apache.org> on 2019/09/12 11:44:00 UTC
[jira] [Created] (ARROW-6548) [Python] consistently handle
conversion of all-NaN arrays across types
Joris Van den Bossche created ARROW-6548:
--------------------------------------------
Summary: [Python] consistently handle conversion of all-NaN arrays across types
Key: ARROW-6548
URL: https://issues.apache.org/jira/browse/ARROW-6548
Project: Apache Arrow
Issue Type: Bug
Components: Python
Reporter: Joris Van den Bossche
In ARROW-5682 (https://github.com/apache/arrow/pull/5333), next to fixing actual conversion bugs, I added the ability to convert all-NaN float arrays when converting to string type (and only with {{from_pandas=True}}). So this now works:
{code}
>>> pa.array(np.array([np.nan, np.nan], dtype=float), type=pa.string())
<pyarrow.lib.StringArray object at 0x7f54dc9de830>
[
null,
null
]
{code}
However, I only added this for string type (and it already works for float and int types). If we are happy with this behaviour, we should also add it for other types.
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