[jira] [Created] (ARROW-17925) [Python] Use ExtensionScalar.as_py() as fallback in ExtensionArray to_pandas?

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

Joris Van den Bossche created ARROW-17925:
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             Summary: [Python] Use ExtensionScalar.as_py() as fallback in ExtensionArray to_pandas?
                 Key: ARROW-17925
                 URL: https://issues.apache.org/jira/browse/ARROW-17925
             Project: Apache Arrow
          Issue Type: Improvement
          Components: Python
            Reporter: Joris Van den Bossche


This was raised in ARROW-17813 by [~changhiskhan]:

{quote}*ExtensionArray => pandas*

Just for discussion, I was curious whether you had any thoughts around using the extension scalar as a fallback mechanism. It's a lot simpler to define an ExtensionScalar with `as_py` than a pandas extension dtype. So if an ExtensionArray doesn't have an equivalent pandas dtype, would it make sense to convert it to just an object series whose elements are the result of `as_py`? {quote}

and I also mentioned this in ARROW-17535:

{quote}That actually brings up a question: if an ExtensionType defines an ExtensionScalar (but not an associciated pandas dtype, or custom to_numpy conversion), should we use this scalar's {{as_py()}} for the to_numpy/to_pandas conversion as well for plain extension arrays? (not the nested case) 

Because currently, if you have an ExtensionArray like that (for example using the example from the docs: https://arrow.apache.org/docs/dev/python/extending_types.html#custom-scalar-conversion), we still use the storage type conversion for to_numpy/to_pandas, and only use the scalar's conversion in {{to_pylist}}.{quote}



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