BUG: df.iloc[ndarray, ndarray] = 2dvals raising with EA column (#44714)

Author: jbrockmendel

doc/source/whatsnew/v1.4.0.rst

@@ -715,6 +715,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc.__setitem__` and :meth:`DataFrame.iloc.__setitem__` with mixed dtypes sometimes failing to operate in-place (:issue:`44345`)
 - Bug in :meth:`DataFrame.loc.__getitem__` incorrectly raising ``KeyError`` when selecting a single column with a boolean key (:issue:`44322`).
 - Bug in setting :meth:`DataFrame.iloc` with a single ``ExtensionDtype`` column and setting 2D values e.g. ``df.iloc[:] = df.values`` incorrectly raising (:issue:`44514`)
+- Bug in setting values with :meth:`DataFrame.iloc` with a single ``ExtensionDtype`` column and a tuple of arrays as the indexer (:issue:`44703`)
 - Bug in indexing on columns with ``loc`` or ``iloc`` using a slice with a negative step with ``ExtensionDtype`` columns incorrectly raising (:issue:`44551`)
 - Bug in :meth:`DataFrame.loc.__setitem__` changing dtype when indexer was completely ``False`` (:issue:`37550`)
 - Bug in :meth:`IntervalIndex.get_indexer_non_unique` returning boolean mask instead of array of integers for a non unique and non monotonic index (:issue:`44084`)

pandas/core/internals/blocks.py

@@ -1512,6 +1512,14 @@ def setitem(self, indexer, value):
             # TODO(EA2D): not needed with 2D EAs
             # we are always 1-D
             indexer = indexer[0]
+            if isinstance(indexer, np.ndarray) and indexer.ndim == 2:
+                # GH#44703
+                if indexer.shape[1] != 1:
+                    raise NotImplementedError(
+                        "This should not be reached. Please report a bug at "
+                        "github.com/pandas-dev/pandas/"
+                    )
+                indexer = indexer[:, 0]
 
         # TODO(EA2D): not needed with 2D EAS
         if isinstance(value, (np.ndarray, ExtensionArray)) and value.ndim == 2:

pandas/tests/indexing/test_iloc.py

@@ -1157,6 +1157,14 @@ def test_iloc_getitem_slice_negative_step_ea_block(self):
         expected = DataFrame({"B": df["B"], "A": df["A"]})
         tm.assert_frame_equal(res, expected)
 
+    def test_iloc_setitem_2d_ndarray_into_ea_block(self):
+        # GH#44703
+        df = DataFrame({"status": ["a", "b", "c"]}, dtype="category")
+        df.iloc[np.array([0, 1]), np.array([0])] = np.array([["a"], ["a"]])
+
+        expected = DataFrame({"status": ["a", "a", "c"]}, dtype=df["status"].dtype)
+        tm.assert_frame_equal(df, expected)
+
 
 class TestILocErrors:
     # NB: this test should work for _any_ Series we can pass as