REF: simplify setitem_with_indexer (#37881)

Author: jbrockmendel

pandas/core/indexing.py

@@ -1647,6 +1647,8 @@ def _setitem_with_indexer_split_path(self, indexer, value):
             indexer = _tuplify(self.ndim, indexer)
         if len(indexer) > self.ndim:
             raise IndexError("too many indices for array")
+        if isinstance(indexer[0], np.ndarray) and indexer[0].ndim > 2:
+            raise ValueError(r"Cannot set values with ndim > 2")
 
         if isinstance(value, ABCSeries):
             value = self._align_series(indexer, value)
@@ -1658,57 +1660,45 @@ def _setitem_with_indexer_split_path(self, indexer, value):
         lplane_indexer = length_of_indexer(pi, self.obj.index)
         # lplane_indexer gives the expected length of obj[indexer[0]]
 
-        if len(ilocs) == 1:
-            # We can operate on a single column
-
-            # require that we are setting the right number of values that
-            # we are indexing
-            if is_list_like_indexer(value) and 0 != lplane_indexer != len(value):
-                # Exclude zero-len for e.g. boolean masking that is all-false
-                raise ValueError(
-                    "cannot set using a multi-index "
-                    "selection indexer with a different "
-                    "length than the value"
-                )
-
         # we need an iterable, with a ndim of at least 1
         # eg. don't pass through np.array(0)
         if is_list_like_indexer(value) and getattr(value, "ndim", 1) > 0:
 
-            # we have an equal len Frame
             if isinstance(value, ABCDataFrame):
                 self._setitem_with_indexer_frame_value(indexer, value)
 
-            # we have an equal len ndarray/convertible to our ilocs
-            # hasattr first, to avoid coercing to ndarray without reason.
-            # But we may be relying on the ndarray coercion to check ndim.
-            # Why not just convert to an ndarray earlier on if needed?
             elif np.ndim(value) == 2:
                 self._setitem_with_indexer_2d_value(indexer, value)
 
             elif len(ilocs) == 1 and lplane_indexer == len(value) and not is_scalar(pi):
-                # we have an equal len list/ndarray
-                # We only get here with len(ilocs) == 1
+                # We are setting multiple rows in a single column.
                 self._setitem_single_column(ilocs[0], value, pi)
 
+            elif len(ilocs) == 1 and 0 != lplane_indexer != len(value):
+                # We are trying to set N values into M entries of a single
+                #  column, which is invalid for N != M
+                # Exclude zero-len for e.g. boolean masking that is all-false
+                raise ValueError(
+                    "Must have equal len keys and value "
+                    "when setting with an iterable"
+                )
+
             elif lplane_indexer == 0 and len(value) == len(self.obj.index):
                 # We get here in one case via .loc with a all-False mask
                 pass
 
-            else:
-                # per-label values
-                if len(ilocs) != len(value):
-                    raise ValueError(
-                        "Must have equal len keys and value "
-                        "when setting with an iterable"
-                    )
-
+            elif len(ilocs) == len(value):
+                # We are setting multiple columns in a single row.
                 for loc, v in zip(ilocs, value):
                     self._setitem_single_column(loc, v, pi)
-        else:
 
-            if isinstance(indexer[0], np.ndarray) and indexer[0].ndim > 2:
-                raise ValueError(r"Cannot set values with ndim > 2")
+            else:
+                raise ValueError(
+                    "Must have equal len keys and value "
+                    "when setting with an iterable"
+                )
+
+        else:
 
             # scalar value
             for loc in ilocs:

pandas/tests/indexing/multiindex/test_setitem.py

@@ -203,10 +203,7 @@ def test_multiindex_assignment(self):
         tm.assert_series_equal(df.loc[4, "c"], exp)
 
         # invalid assignments
-        msg = (
-            "cannot set using a multi-index selection indexer "
-            "with a different length than the value"
-        )
+        msg = "Must have equal len keys and value when setting with an iterable"
         with pytest.raises(ValueError, match=msg):
             df.loc[4, "c"] = [0, 1, 2, 3]
 

pandas/tests/indexing/test_indexing.py

@@ -33,10 +33,7 @@ def test_setitem_ndarray_1d(self):
         df["bar"] = np.zeros(10, dtype=complex)
 
         # invalid
-        msg = (
-            "cannot set using a multi-index selection "
-            "indexer with a different length than the value"
-        )
+        msg = "Must have equal len keys and value when setting with an iterable"
         with pytest.raises(ValueError, match=msg):
             df.loc[df.index[2:5], "bar"] = np.array([2.33j, 1.23 + 0.1j, 2.2, 1.0])