BUG: array ufuncs with more than 2 inputs fails with 2 or more pd.Series and scalar arguments

doc/source/whatsnew/v1.6.0.rst

@@ -189,7 +189,7 @@ Timezones
 
 Numeric
 ^^^^^^^
--
+- Bug in :meth:`DataFrame.add` cannot apply ufunc when inputs contain mixed DataFrame type and Series type (:issue:`39853`)
 -
 
 Conversion

pandas/core/arraylike.py

@@ -250,6 +250,10 @@ def array_ufunc(self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any)
     --------
     numpy.org/doc/stable/reference/arrays.classes.html#numpy.class.__array_ufunc__
     """
+    from pandas.core.frame import (
+        DataFrame,
+        Series,
+    )
     from pandas.core.generic import NDFrame
     from pandas.core.internals import BlockManager
 
@@ -295,8 +299,8 @@ def array_ufunc(self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any)
         # At the moment, there aren't any ufuncs with more than two inputs
         # so this ends up just being x1.index | x2.index, but we write
         # it to handle *args.
-
-        if len(set(types)) > 1:
+        set_types = set(types)
+        if len(set_types) > 1 and {DataFrame, Series}.issubset(set_types):
             # We currently don't handle ufunc(DataFrame, Series)
             # well. Previously this raised an internal ValueError. We might
             # support it someday, so raise a NotImplementedError.

pandas/tests/frame/test_ufunc.py

@@ -1,4 +1,5 @@
 from functools import partial
+import re
 
 import numpy as np
 import pytest
@@ -301,3 +302,24 @@ def my_ufunc(x, y, z):
         result = my_ufunc(df1.values, df2, df3)
     expected = expected.set_axis(["b", "c"], axis=1)
     tm.assert_frame_equal(result, expected)
+
+
+def test_array_ufuncs_for_many_arguments():
+    # GH39853
+    def add3(x, y, z):
+        return x + y + z
+
+    ufunc = np.frompyfunc(add3, 3, 1)
+    df = pd.DataFrame([[1, 2], [3, 4]])
+
+    result = ufunc(df, df, 1)
+    expected = pd.DataFrame([[3, 5], [7, 9]], dtype=object)
+    tm.assert_frame_equal(result, expected)
+
+    ser = pd.Series([1, 2])
+    msg = (
+        "Cannot apply ufunc <ufunc 'add3 (vectorized)'> "
+        "to mixed DataFrame and Series inputs."
+    )
+    with pytest.raises(NotImplementedError, match=re.escape(msg)):
+        ufunc(df, df, ser)

pandas/tests/series/test_ufunc.py

@@ -1,4 +1,5 @@
 from collections import deque
+import re
 import string
 
 import numpy as np
@@ -453,3 +454,25 @@ def test_np_matmul():
         expected_result,
         result,
     )
+
+
+def test_array_ufuncs_for_many_arguments():
+    # GH39853
+    def add3(x, y, z):
+        return x + y + z
+
+    ufunc = np.frompyfunc(add3, 3, 1)
+    ser = pd.Series([1, 2])
+
+    result = ufunc(ser, ser, 1)
+    expected = pd.Series([3, 5], dtype=object)
+    tm.assert_series_equal(result, expected)
+
+    df = pd.DataFrame([[1, 2]])
+
+    msg = (
+        "Cannot apply ufunc <ufunc 'add3 (vectorized)'> "
+        "to mixed DataFrame and Series inputs."
+    )
+    with pytest.raises(NotImplementedError, match=re.escape(msg)):
+        ufunc(ser, ser, df)