feat(checker): try to filter groupby columns
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@@ -598,8 +598,48 @@ class FrameMethodRegistry(MethodRegistry[Call]):
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)
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)
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return result.result
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return result.result
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def _filter_groupby_columns(
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self, frame: DataFrameType, by: TypedExpr
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) -> DataFrameType:
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by_columns: list[str] = []
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by_expr, _ = by
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if not isinstance(by_expr, p.ListExpr):
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return frame
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for item in by_expr.items:
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match item:
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case p.LiteralExpr(value=str() as name):
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by_columns.append(name)
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new_columns: list[DataFrameType.Column] = []
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for column in frame.columns:
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if column.name in by_columns:
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continue
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new_columns.append(
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DataFrameType.Column(
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index=len(new_columns),
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name=column.name,
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type=column.type,
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)
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)
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return DataFrameType(columns=new_columns)
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@method()
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@method()
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def groupby(self, call: Call) -> Type:
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def groupby(self, call: Call) -> Type:
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new_frame: DataFrameType = call.frame
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by: Optional[TypedExpr] = None
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if len(call.positional) != 0:
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by = call.positional[0]
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elif "by" in call.keywords:
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by = call.keywords["by"]
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if by is not None:
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new_frame = self._filter_groupby_columns(call.frame, by)
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bool_: Type = self.types.get_type("bool")
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bool_: Type = self.types.get_type("bool")
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function: Function = Function(
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function: Function = Function(
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params=ParamSpec(
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params=ParamSpec(
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@@ -629,7 +669,7 @@ class FrameMethodRegistry(MethodRegistry[Call]):
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)
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)
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],
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],
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),
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),
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returns=FrameGroupBy(frame=call.frame),
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returns=FrameGroupBy(frame=new_frame),
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)
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)
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result: CallResult = self.dispatcher.get_result(
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result: CallResult = self.dispatcher.get_result(
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