[jira] [Updated] (ARROW-6548) [Python] consistently handle conversion of all-NaN arrays across types

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-6548?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joris Van den Bossche updated ARROW-6548:
-----------------------------------------
    Fix Version/s:     (was: 6.0.0)
                   7.0.0

> [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
>            Priority: Major
>             Fix For: 7.0.0
>
>
> 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(), from_pandas=True)
> <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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