BUG: Fix calling groupBy(...).apply(func) on an empty dataframe invokes func

pandas/core/groupby/ops.py

@@ -844,18 +844,22 @@ def apply(
             if not mutated and not _is_indexed_like(res, group_axes, axis):
                 mutated = True
             result_values.append(res)
-
         # getattr pattern for __name__ is needed for functools.partial objects
         if len(group_keys) == 0 and getattr(f, "__name__", None) not in [
             "idxmin",
             "idxmax",
             "nanargmin",
             "nanargmax",
         ]:
-            # If group_keys is empty, then no function calls have been made,
-            #  so we will not have raised even if this is an invalid dtype.
-            #  So do one dummy call here to raise appropriate TypeError.
-            f(data.iloc[:0])
+            try:
+                #  If group_keys is empty, then no function calls have been made,
+                #  so we will not have raised even if this is an invalid dtype.
+                #  So do one dummy call here to raise appropriate TypeError.
+                f(data.iloc[:0])
+            except IndexError:
+                # If IndexError is raised,
+                # maintain consistency for all operations on empty groups
+                pass
 
         return result_values, mutated
 

pandas/tests/groupby/test_apply.py

@@ -1331,3 +1331,13 @@ def test_result_name_when_one_group(name):
     expected = Series([1, 2], name=name)
 
     tm.assert_series_equal(result, expected)
+
+
+def test_empty_df():
+    empty_df = DataFrame({"a": [], "b": []})
+
+    # Both operations should return an empty series instead of IndexError for apply UDF
+    result = empty_df.groupby("a").b.apply(lambda x: x.values[-1])
+    expected = empty_df.groupby("a").b.agg("sum")
+
+    tm.assert_series_equal(result, expected)