REGR: ufunc with DataFrame input not passing all kwargs

doc/source/whatsnew/v1.2.4.rst

@@ -21,6 +21,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.where` not returning a copy in the case of an all True condition (:issue:`39595`)
 - Fixed regression in :meth:`DataFrame.replace` raising ``IndexError`` when ``regex`` was a multi-key dictionary (:issue:`39338`)
 - Fixed regression in repr of floats in an ``object`` column not respecting ``float_format`` when printed in the console or outputted through :meth:`DataFrame.to_string`, :meth:`DataFrame.to_html`, and :meth:`DataFrame.to_latex` (:issue:`40024`)
+- Fixed regression in ``numpy`` ufuncs such as ``np.add`` not passing through all arguments for 2-dimensional input (:issue:`40662`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/arraylike.py

@@ -357,7 +357,7 @@ def reconstruct(result):
         # * len(inputs) > 1 is doable when we know that we have
         #   aligned blocks / dtypes.
         inputs = tuple(np.asarray(x) for x in inputs)
-        result = getattr(ufunc, method)(*inputs)
+        result = getattr(ufunc, method)(*inputs, **kwargs)
     elif self.ndim == 1:
         # ufunc(series, ...)
         inputs = tuple(extract_array(x, extract_numpy=True) for x in inputs)

pandas/tests/frame/test_ufunc.py

@@ -60,6 +60,22 @@ def test_binary_input_dispatch_binop(dtype):
     tm.assert_frame_equal(result, expected)
 
 
+def test_ufunc_passes_args():
+    # GH#40662
+    arr = np.array([[1, 2], [3, 4]])
+    df = pd.DataFrame(arr)
+    result = np.zeros_like(df)
+    np.add(df, 1, out=result)
+
+    expected = arr + 1
+    tm.assert_numpy_array_equal(result, expected)
+
+    result = np.zeros_like(df)
+    np.add(df, 1, out=result, where=[[False, True], [True, False]])
+    expected = np.array([[0, 3], [4, 0]])
+    tm.assert_numpy_array_equal(result, expected)
+
+
 @pytest.mark.parametrize("dtype_a", dtypes)
 @pytest.mark.parametrize("dtype_b", dtypes)
 def test_binary_input_aligns_columns(request, dtype_a, dtype_b):