ERR: error handling in DataFrame.__rmatmul__ (#36792)

Author: jbrockmendel

doc/source/whatsnew/v1.2.0.rst

@@ -327,7 +327,7 @@ Numeric
 - Bug in :meth:`Series.equals` where a ``ValueError`` was raised when numpy arrays were compared to scalars (:issue:`35267`)
 - Bug in :class:`Series` where two :class:`Series` each have a :class:`DatetimeIndex` with different timezones having those indexes incorrectly changed when performing arithmetic operations (:issue:`33671`)
 - Bug in :meth:`pd._testing.assert_almost_equal` was incorrect for complex numeric types (:issue:`28235`)
--
+- Bug in :meth:`DataFrame.__rmatmul__` error handling reporting transposed shapes (:issue:`21581`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/frame.py

@@ -1216,7 +1216,14 @@ def __rmatmul__(self, other):
         """
         Matrix multiplication using binary `@` operator in Python>=3.5.
         """
-        return self.T.dot(np.transpose(other)).T
+        try:
+            return self.T.dot(np.transpose(other)).T
+        except ValueError as err:
+            if "shape mismatch" not in str(err):
+                raise
+            # GH#21581 give exception message for original shapes
+            msg = f"shapes {np.shape(other)} and {self.shape} not aligned"
+            raise ValueError(msg) from err
 
     # ----------------------------------------------------------------------
     # IO methods (to / from other formats)

pandas/tests/frame/test_analytics.py

@@ -1177,6 +1177,20 @@ def test_matmul(self):
         with pytest.raises(ValueError, match="aligned"):
             operator.matmul(df, df2)
 
+    def test_matmul_message_shapes(self):
+        # GH#21581 exception message should reflect original shapes,
+        #  not transposed shapes
+        a = np.random.rand(10, 4)
+        b = np.random.rand(5, 3)
+
+        df = DataFrame(b)
+
+        msg = r"shapes \(10, 4\) and \(5, 3\) not aligned"
+        with pytest.raises(ValueError, match=msg):
+            a @ df
+        with pytest.raises(ValueError, match=msg):
+            a.tolist() @ df
+
     # ---------------------------------------------------------------------
     # Unsorted