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  • closes #xxxx (Replace xxxx with the Github issue number)
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class NumericDtype(BaseMaskedDtype):
_default_np_dtype: np.dtype
_checker: Callable[[Any], bool] # is_foo_dtype
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I'd be more partial to _dtype_checker, but won't die on that hill

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sure. OK for follow-up?

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Yup sounds good

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Off-topic question: I am interested in exploring the feasibility of adding an Arrow-back NumericArray. It doesn't appear that I can just subclass this since NumericArray and it's subclass are heavily numpy based.

Any recommendations on where to start? Would I need to essentially create MaskedArrowArray and go from there?

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Any recommendations on where to start? Would I need to essentially create MaskedArrowArray and go from there?

I've been thinking we should refactor as much of ArrowStringArray as possible out into a general arrow-backed EA. Not sure if that could be a fully-formed EA or if it would need to be a mixin. (also in the tests there's an ArrowExtensionArray but I think its half-baked)

FWIW my current thought with MaskedArray is to try to get as much of NumericArray and BooleanArray pushed down into MaskedArray as possible so it can just become a wrapper around an arbitrary non-masked array (including e.g. other EAs)

@mroeschke mroeschke added NA - MaskedArrays Related to pd.NA and nullable extension arrays Refactor Internal refactoring of code labels Feb 15, 2022
@mroeschke mroeschke added this to the 1.5 milestone Feb 15, 2022
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Thanks for the gameplan. LGTM.

@jreback jreback merged commit cf2dfa7 into pandas-dev:main Feb 16, 2022
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jreback commented Feb 16, 2022

luv it

@jbrockmendel jbrockmendel deleted the ref-masked branch February 16, 2022 15:45
yehoshuadimarsky pushed a commit to yehoshuadimarsky/pandas that referenced this pull request Jul 13, 2022
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NA - MaskedArrays Related to pd.NA and nullable extension arrays Refactor Internal refactoring of code

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3 participants