[jira] [Updated] (ARROW-7168) [Python] pa.array() doesn't respect provided dictionary type with all NaNs

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

     [ https://issues.apache.org/jira/browse/ARROW-7168?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joris Van den Bossche updated ARROW-7168:
-----------------------------------------
    Summary: [Python] pa.array() doesn't respect provided dictionary type with all NaNs  (was: pa.array() doesn't respect provided dictionary type with all NaNs)

> [Python] pa.array() doesn't respect provided dictionary type with all NaNs
> --------------------------------------------------------------------------
>
>                 Key: ARROW-7168
>                 URL: https://issues.apache.org/jira/browse/ARROW-7168
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: C++, Python
>    Affects Versions: 0.15.1
>            Reporter: Thomas Buhrmann
>            Priority: Major
>
> This might be related to ARROW-6548 and others dealing with all NaN columns. When creating a dictionary array, even when fully specifying the desired type, this type is not respected when the data contains only NaNs:
> {code:python}
> # This may look a little artificial but easily occurs when processing categorial data in batches and a particular batch containing only NaNs
> ser = pd.Series([None, None]).astype('object').astype('category')
> typ = pa.dictionary(index_type=pa.int8(), value_type=pa.string(), ordered=False)
> pa.array(ser, type=typ).type
> {code}
> results in
> {noformat}
> >> DictionaryType(dictionary<values=null, indices=int8, ordered=0>)
> {noformat}
> which means that one cannot e.g. serialize batches of categoricals if the possibility of all-NaN batches exists, even when trying to enforce that each batch has the same schema (because the schema is not respected).
> I understand that inferring the type in this case would be difficult, but I'd imagine that a fully specified type should be respected in this case?
> In the meantime, is there a workaround to manually create a dictionary array of the desired type containing only NaNs?



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