wip

Author: MarcoGorelli

pandas/tests/frame/methods/test_update.py

@@ -148,22 +148,6 @@ def test_update_datetime_tz_in_place(self):
         tm.assert_frame_equal(result, expected)
         tm.assert_frame_equal(view, orig)
 
-    def test_update_with_different_dtype(self):
-        # GH#3217
-        df = DataFrame({"a": [1, 3], "b": [np.nan, 2]})
-        df["c"] = np.nan
-        with tm.assert_produces_warning(FutureWarning, match="incompatible dtype"):
-            df.update({"c": Series(["foo"], index=[0])})
-
-        expected = DataFrame(
-            {
-                "a": [1, 3],
-                "b": [np.nan, 2],
-                "c": Series(["foo", np.nan], dtype="object"),
-            }
-        )
-        tm.assert_frame_equal(df, expected)
-
     def test_update_modify_view(self, using_infer_string):
         # GH#47188
         df = DataFrame({"A": ["1", np.nan], "B": ["100", np.nan]})

pandas/tests/indexing/multiindex/test_setitem.py

@@ -212,18 +212,9 @@ def test_multiindex_assignment_single_dtype(self):
         result = df.loc[4, "c"]
         tm.assert_series_equal(result, exp)
 
-        # arr + 0.5 cannot be cast losslessly to int, so we upcast
-        with tm.assert_produces_warning(
-            FutureWarning, match="item of incompatible dtype"
-        ):
-            df.loc[4, "c"] = arr + 0.5
-        result = df.loc[4, "c"]
-        exp = exp + 0.5
-        tm.assert_series_equal(result, exp)
-
         # scalar ok
         df.loc[4, "c"] = 10
-        exp = Series(10, index=[8, 10], name="c", dtype="float64")
+        exp = Series(10, index=[8, 10], name="c")
         tm.assert_series_equal(df.loc[4, "c"], exp)
 
         # invalid assignments