PERF: Try fast/slow paths only once in DataFrameGroupby.transform

pandas/core/groupby/generic.py

@@ -1308,29 +1308,9 @@ def _transform_general(self, func, *args, **kwargs):
         gen = self.grouper.get_iterator(obj, axis=self.axis)
         fast_path, slow_path = self._define_paths(func, *args, **kwargs)
 
-        def process_result(
-            group: DataFrame | Series, res: DataFrame | Series
-        ) -> DataFrame | Series:
-            if isinstance(res, Series):
-                # we need to broadcast across the
-                # other dimension; this will preserve dtypes
-                # GH14457
-                if res.index.is_(obj.index):
-                    r = concat([res] * len(group.columns), axis=1)
-                    r.columns = group.columns
-                    r.index = group.index
-                else:
-                    r = self.obj._constructor(
-                        np.concatenate([res.values] * len(group.index)).reshape(
-                            group.shape
-                        ),
-                        columns=group.columns,
-                        index=group.index,
-                    )
-                return r
-            else:
-                return res
-
+        # Determine whether to use slow or fast path by evaluating on the first group.
+        # Need to handle the case of an empty generator and process the result so that
+        # it does not need to be computed again.
         try:
             name, group = next(gen)
         except StopIteration:
@@ -1345,14 +1325,17 @@ def process_result(
                 msg = "transform must return a scalar value for each group"
                 raise ValueError(msg) from err
             if group.size > 0:
-                applied.append(process_result(group, res))
+                res = _wrap_transform_general_frame(self.obj, group, res)
+                applied.append(res)
 
+        # Compute and process with the remaining groups
         for name, group in gen:
             if group.size == 0:
                 continue
             object.__setattr__(group, "name", name)
             res = path(group)
-            applied.append(process_result(group, res))
+            res = _wrap_transform_general_frame(self.obj, group, res)
+            applied.append(res)
 
         concat_index = obj.columns if self.axis == 0 else obj.index
         other_axis = 1 if self.axis == 0 else 0  # switches between 0 & 1
@@ -1863,3 +1846,28 @@ def func(df):
         return self._python_apply_general(func, self._obj_with_exclusions)
 
     boxplot = boxplot_frame_groupby
+
+
+def _wrap_transform_general_frame(
+    obj: DataFrame, group: DataFrame, res: DataFrame | Series
+) -> DataFrame:
+    from pandas import concat
+
+    if isinstance(res, Series):
+        # we need to broadcast across the
+        # other dimension; this will preserve dtypes
+        # GH14457
+        if res.index.is_(obj.index):
+            r = concat([res] * len(group.columns), axis=1)
+            r.columns = group.columns
+            r.index = group.index
+        else:
+            r = obj._constructor(
+                np.concatenate([res.values] * len(group.index)).reshape(group.shape),
+                columns=group.columns,
+                index=group.index,
+            )
+        assert isinstance(r, DataFrame)
+        return r
+    else:
+        return res