wip

Author: MarcoGorelli

pandas/tests/frame/indexing/test_indexing.py

@@ -1879,22 +1879,30 @@ def test_add_new_column_infer_string():
 class TestSetitemValidation:
     # This is adapted from pandas/tests/arrays/masked/test_indexing.py
     # but checks for warnings instead of errors.
-    def _check_setitem_invalid(self, df, invalid, indexer, warn):
-        msg = "Setting an item of incompatible dtype is deprecated"
-        msg = re.escape(msg)
-
+    def _check_setitem_invalid(self, df, invalid, indexer):
         orig_df = df.copy()
 
         # iloc
-        with tm.assert_produces_warning(warn, match=msg):
+        with pytest.raises(TypeError, match="Invalid value"):
             df.iloc[indexer, 0] = invalid
             df = orig_df.copy()
 
         # loc
-        with tm.assert_produces_warning(warn, match=msg):
+        with pytest.raises(TypeError, match="Invalid value"):
             df.loc[indexer, "a"] = invalid
             df = orig_df.copy()
 
+    def _check_setitem_valid(self, df, invalid, indexer):
+        orig_df = df.copy()
+
+        # iloc
+        df.iloc[indexer, 0] = invalid
+        df = orig_df.copy()
+
+        # loc
+        df.loc[indexer, "a"] = invalid
+        df = orig_df.copy()
+
     _invalid_scalars = [
         1 + 2j,
         "True",
@@ -1912,20 +1920,19 @@ def _check_setitem_invalid(self, df, invalid, indexer, warn):
     @pytest.mark.parametrize("indexer", _indexers)
     def test_setitem_validation_scalar_bool(self, invalid, indexer):
         df = DataFrame({"a": [True, False, False]}, dtype="bool")
-        self._check_setitem_invalid(df, invalid, indexer, FutureWarning)
+        self._check_setitem_invalid(df, invalid, indexer)
 
     @pytest.mark.parametrize("invalid", _invalid_scalars + [True, 1.5, np.float64(1.5)])
     @pytest.mark.parametrize("indexer", _indexers)
     def test_setitem_validation_scalar_int(self, invalid, any_int_numpy_dtype, indexer):
         df = DataFrame({"a": [1, 2, 3]}, dtype=any_int_numpy_dtype)
         if isna(invalid) and invalid is not pd.NaT and not np.isnat(invalid):
-            warn = None
+            self._check_setitem_valid(df, invalid, indexer)
         else:
-            warn = FutureWarning
-        self._check_setitem_invalid(df, invalid, indexer, warn)
+            self._check_setitem_invalid(df, invalid, indexer)
 
     @pytest.mark.parametrize("invalid", _invalid_scalars + [True])
     @pytest.mark.parametrize("indexer", _indexers)
     def test_setitem_validation_scalar_float(self, invalid, float_numpy_dtype, indexer):
         df = DataFrame({"a": [1, 2, None]}, dtype=float_numpy_dtype)
-        self._check_setitem_invalid(df, invalid, indexer, FutureWarning)
+        self._check_setitem_invalid(df, invalid, indexer)