refactor: complete dtype rules for expression tree transformations #376
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| 3 <NA> | ||
| 4 <NA> | ||
| dtype: Float64 | ||
| dtype: Int64 |
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Good to see that this change fix this issue!
bigframes/session/__init__.py
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| inline_df = dataframe.DataFrame( | ||
| blocks.Block.from_local(pandas_dataframe, self) | ||
| ) | ||
| except ValueError: # Thrown by ibis for some unhandled tyeps |
| @@ -146,6 +205,24 @@ def skips_nulls(self): | |||
| def handles_ties(self): | |||
| return True | |||
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| def output_type(self, *input_types: dtypes.ExpressionType): | |||
| if isinstance(self.bins, int) and (self.labels is False): | |||
| return dtypes.INT_DTYPE | |||
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do you have a chance to test it? Is it FLOAT_DTYPE?
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yes, the test suite automatically validates all these derivations now
bigframes/operations/aggregations.py
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| @dataclasses.dataclass(frozen=True) | ||
| class MeanOp(UnaryAggregateOp): | ||
| name: ClassVar[str] = "mean" | ||
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| def output_type(self, *input_types: dtypes.ExpressionType): | ||
| if pd.api.types.is_bool_dtype(input_types[0]): |
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nit:
if pd.api.types.is_bool_dtype(input_types[0]) or pd.api.types.is_integer_dtype(input_types[0]):
return dtypes.FLOAT_DTYPE
bigframes/operations/aggregations.py
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| @@ -87,16 +112,38 @@ class ApproxQuartilesOp(UnaryAggregateOp): | |||
| def name(self): | |||
| return f"{self.quartile*25}%" | |||
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| def output_type(self, *input_types: dtypes.ExpressionType): | |||
| if pd.api.types.is_bool_dtype(input_types[0]): | |||
| if not isinstance(x, ibis_types.DecimalValue): | ||
| return False | ||
| # Should be exactly 76 for bignumeric | ||
| return x.precision > 70 |
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Can you update it into == 76 as you handle the numeric casting at line 1102 in this line?
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I care about the pre-cast type information, and I don't trust ibis to have the precision/scale numbers right.
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Fixes #<issue_number_goes_here> 🦕