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Dtype ConversionsUnexpected or buggy dtype conversionsUnexpected or buggy dtype conversionsExtensionArrayExtending pandas with custom dtypes or arrays.Extending pandas with custom dtypes or arrays.Missing-datanp.nan, pd.NaT, pd.NA, dropna, isnull, interpolatenp.nan, pd.NaT, pd.NA, dropna, isnull, interpolateNumeric OperationsArithmetic, Comparison, and Logical operationsArithmetic, Comparison, and Logical operations
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xref #8640
Could easily imagine an ExtensionArray
which uses as an implementation a numpy array of the appropriate dtype and a bitmask in order to fully support Integer NA across the board. I don't think this would be too hard. As a bonus, would be zero-copy compat with pyarrow impl (for the future)
- Integer (ENH: Integer NA Extension Array #21160)
- UnsignedInteger (ENH: Integer NA Extension Array #21160)
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Boolean(API: boolean Extension Array #21778)
making these the actual default (e.g. when integers are inferred with or w/o nulls) might be non-trivial, but let's implement first. These would give rise to a hierarchy of dtypes, e.g. IntegerDtype
, Int8Dtype
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Dtype ConversionsUnexpected or buggy dtype conversionsUnexpected or buggy dtype conversionsExtensionArrayExtending pandas with custom dtypes or arrays.Extending pandas with custom dtypes or arrays.Missing-datanp.nan, pd.NaT, pd.NA, dropna, isnull, interpolatenp.nan, pd.NaT, pd.NA, dropna, isnull, interpolateNumeric OperationsArithmetic, Comparison, and Logical operationsArithmetic, Comparison, and Logical operations