REF: BaseGroupBy methods belong in GroupBy (pandas-dev#41066)

Author: jbrockmendel

pandas/core/groupby/generic.py

@@ -345,6 +345,49 @@ def _aggregate_multiple_funcs(self, arg):
         )
         return self.obj._constructor_expanddim(output, columns=columns)
 
+    def _cython_agg_general(
+        self, how: str, alt=None, numeric_only: bool = True, min_count: int = -1
+    ):
+        output: dict[base.OutputKey, ArrayLike] = {}
+        # Ideally we would be able to enumerate self._iterate_slices and use
+        # the index from enumeration as the key of output, but ohlc in particular
+        # returns a (n x 4) array. Output requires 1D ndarrays as values, so we
+        # need to slice that up into 1D arrays
+        idx = 0
+        for obj in self._iterate_slices():
+            name = obj.name
+            is_numeric = is_numeric_dtype(obj.dtype)
+            if numeric_only and not is_numeric:
+                continue
+
+            result = self.grouper._cython_operation(
+                "aggregate", obj._values, how, axis=0, min_count=min_count
+            )
+
+            if how == "ohlc":
+                # e.g. ohlc
+                agg_names = ["open", "high", "low", "close"]
+                assert len(agg_names) == result.shape[1]
+                for result_column, result_name in zip(result.T, agg_names):
+                    key = base.OutputKey(label=result_name, position=idx)
+                    output[key] = result_column
+                    idx += 1
+            else:
+                assert result.ndim == 1
+                key = base.OutputKey(label=name, position=idx)
+                output[key] = result
+                idx += 1
+
+        if not output:
+            raise DataError("No numeric types to aggregate")
+
+        # error: Argument 1 to "_wrap_aggregated_output" of "BaseGroupBy" has
+        # incompatible type "Dict[OutputKey, Union[ndarray, DatetimeArray]]";
+        # expected "Mapping[OutputKey, ndarray]"
+        return self._wrap_aggregated_output(
+            output, index=self.grouper.result_index  # type: ignore[arg-type]
+        )
+
     # TODO: index should not be Optional - see GH 35490
     def _wrap_series_output(
         self,