Add initial support for converting pandas extension dtypes to arrays #10018
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j-bennet
reviewed
Mar 3, 2023
| @@ -371,7 +372,12 @@ def size(x): | |||
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| def values(df): | |||
| return df.values | |||
| values = df.values | |||
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This is better than throwing an exception. I'd add a warning here. Something like this:
warnings.warn('Dask doesn't have support for X dtype yet. Values were converted from X to object. See issue XXX for more information', UserWarning)
Users might notice the conversion and think it's a bug, that would let them know that there's no need to file an issue.
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Agree with @j-bennet that casting to object is better than an error, and that we should probably warn the user.
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Yeah, agreed that's the most friendly thing to do. I pushed a commit yesterday which adds a warning about converting to object dtype in this case
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Currently when one calls
.valueson a Dask Series / Index that holds extension dtypes, an error along the lines ofTypeError: Cannot interpret 'Float32Dtype()' as a data typeis raised becausenumpydoesn't know how to handle pandas extension dtypes (xref #9401).This PR proposes we add initial support for this case by just converting extension dtypes we encounter to
objects before handing off tonumpy. There are other approaches we could take, for example something like #7375, that would give better parity withpandasbehavior, but casting toobjectfeels like reasonable progress over the status quo of throwing an error.cc @rjzamora @j-bennet for thoughts