BUG: setting dataframe column to 2d array with more than one col

References this issue on Github:
pandas-dev#40827

pandas/core/frame.py

@@ -3843,6 +3843,14 @@ def reindexer(value):
                 else:
                     value = com.asarray_tuplesafe(value)
             elif value.ndim == 2:
+                value_cols = value.shape[1]
+                if value_cols > 1:
+                    raise ValueError(
+                        f"Dataframe column '{key}' is being "
+                        "assigned to a 2D array with more than "
+                        "two columns. Column assignment accepts "
+                        "only 2D arrays with one column."
+                    )
                 value = value.copy().T
             elif isinstance(value, Index):
                 value = value.copy(deep=True)

pandas/tests/frame/indexing/test_setitem.py

@@ -1,3 +1,5 @@
+from hypothesis import given, settings, strategies as st
+from hypothesis.extra.numpy import arrays
 import numpy as np
 import pytest
 
@@ -22,6 +24,29 @@
 
 
 class TestDataFrameSetItem:
+    @settings(max_examples=200)
+    @given(
+        st.one_of(
+            [
+                arrays(dtype=str, shape=(4, 2)),
+                arrays(dtype=float, shape=(4, 2)),
+                arrays(dtype=int, shape=(4, 2)),
+                arrays(dtype=str, shape=(4, 5)),
+                arrays(dtype=float, shape=(4, 5)),
+                arrays(dtype=int, shape=(4, 5)),
+            ]
+        )
+    )
+    def test__setitem_size_incompatible_ndarray(self, arr):
+        data = DataFrame(np.zeros((4, 2)), columns=["A", "B"])
+        msg = (
+            "Dataframe column 'A' is being assigned to a 2D "
+            "array with more than two columns. Column assignment "
+            "accepts only 2D arrays with one column."
+        )
+        with pytest.raises(Exception, match=msg):
+            data["A"] = arr
+
     @pytest.mark.parametrize("dtype", ["int32", "int64", "float32", "float64"])
     def test_setitem_dtype(self, dtype, float_frame):
         arr = np.random.randn(len(float_frame))