Support pandas nullable types. #7760
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hcho3
approved these changes
Mar 29, 2022
Ark-kun
reviewed
Aug 31, 2022
| nullable_alias = {"Int16", "Int32", "Int64"} | ||
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| # dtype: pd.core.arrays.numeric.NumericDtype | ||
| def is_nullable_dtype(dtype: Any) -> bool: |
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Why is this function needed?
It does not seem to make any difference when the same types are in _pandas_dtype_mapper.
Ark-kun
reviewed
Aug 31, 2022
| @@ -293,6 +316,9 @@ def _transform_pandas_df( | |||
| .cat.codes.astype(np.float32) | |||
| .replace(-1.0, np.NaN) | |||
| ) | |||
| elif is_nullable_dtype(dtype): | |||
| # Converts integer <NA> to float NaN | |||
| transformed[data.columns[i]] = data[data.columns[i]].astype(np.float32) | |||
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Is it correct to convert Int64 to float32?
Ark-kun
reviewed
Aug 31, 2022
| is_bool_dtype, | ||
| ) | ||
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| nullable_alias = {"Int16", "Int32", "Int64"} |
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boolean is nullable as well. Either it should be in this set or this set should be renamed.
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cuDF uses nullable type by default, no special support is needed.
Close #6851 .