try fix

Author: jorisvandenbossche

pandas/core/internals/managers.py

@@ -573,11 +573,18 @@ def setitem(self, indexer, value) -> Self:
                         0, blk_loc, values
                     )
                     # first block equals values we are setting to -> set to all columns
-                    col_indexer = slice(None)
+                    if len(blk_loc) > 1:
+                        col_indexer = slice(None)
+                    else:
+                        col_indexer = np.arange(len(blk_loc))
                     row_indexer = indexer[0]
                     if isinstance(row_indexer, np.ndarray) and row_indexer.ndim == 2:
                         # numpy cannot handle a 2d indexer in combo with a slice
                         row_indexer = np.squeeze(row_indexer, axis=1)
+                    if len(row_indexer) == 0:
+                        # numpy does not like empty indexer combined with slice
+                        # and we are setting nothing anyway
+                        return self
                     self.blocks[0].setitem((row_indexer, col_indexer), value)
                     return self
             # No need to split if we either set all columns or on a single block

pandas/tests/frame/methods/test_update.py

@@ -155,14 +155,15 @@ def test_update_with_different_dtype(self):
         with pytest.raises(TypeError, match="Invalid value"):
             df.update({"c": Series(["foo"], index=[0])})
 
-    def test_update_modify_view(self, using_infer_string):
+    @pytest.mark.parametrize("dtype", ["str", object])
+    def test_update_modify_view(self, dtype):
         # GH#47188
-        df = DataFrame({"A": ["1", np.nan], "B": ["100", np.nan]})
-        df2 = DataFrame({"A": ["a", "x"], "B": ["100", "200"]})
+        df = DataFrame({"A": ["1", np.nan], "B": ["100", np.nan]}, dtype=dtype)
+        df2 = DataFrame({"A": ["a", "x"], "B": ["100", "200"]}, dtype=dtype)
         df2_orig = df2.copy()
         result_view = df2[:]
         df2.update(df)
-        expected = DataFrame({"A": ["1", "x"], "B": ["100", "200"]})
+        expected = DataFrame({"A": ["1", "x"], "B": ["100", "200"]}, dtype=dtype)
         tm.assert_frame_equal(df2, expected)
         tm.assert_frame_equal(result_view, df2_orig)
 

pandas/tests/indexing/test_loc.py

@@ -3339,11 +3339,12 @@ def test_loc_index_alignment_for_series(self):
         expected = DataFrame({"a": [999, 200], "b": [3, 4]})
         tm.assert_frame_equal(expected, df)
 
-    def test_loc_reindexing_of_empty_index(self):
+    @pytest.mark.parametrize("dtype", ["str", object])
+    def test_loc_reindexing_of_empty_index(self, dtype):
         # GH 57735
-        df = DataFrame(index=[1, 1, 2, 2], data=["1", "1", "2", "2"])
+        df = DataFrame(index=[1, 1, 2, 2], data=["1", "1", "2", "2"], dtype=dtype)
         df.loc[Series([False] * 4, index=df.index, name=0), 0] = df[0]
-        expected = DataFrame(index=[1, 1, 2, 2], data=["1", "1", "2", "2"])
+        expected = DataFrame(index=[1, 1, 2, 2], data=["1", "1", "2", "2"], dtype=dtype)
         tm.assert_frame_equal(df, expected)
 
     @pytest.mark.parametrize(