DEPR: enforce Series.__setitem__ behavior with Float64Index and non-present int key (#49530)

Author: jbrockmendel

doc/source/whatsnew/v2.0.0.rst

@@ -449,6 +449,7 @@ Removal of prior version deprecations/changes
 - Changed behavior of comparison of ``NaT`` with a ``datetime.date`` object; these now raise on inequality comparisons (:issue:`39196`)
 - Enforced deprecation of silently dropping columns that raised a ``TypeError`` in :class:`Series.transform` and :class:`DataFrame.transform` when used with a list or dictionary (:issue:`43740`)
 - Change behavior of :meth:`DataFrame.apply` with list-like so that any partial failure will raise an error (:issue:`43740`)
+- Changed behavior of :meth:`Series.__setitem__` with an integer key and a :class:`Float64Index` when the key is not present in the index; previously we treated the key as positional (behaving like ``series.iloc[key] = val``), now we treat it is a label (behaving like ``series.loc[key] = val``), consistent with :meth:`Series.__getitem__`` behavior (:issue:`33469`)
 - Removed ``na_sentinel`` argument from :func:`factorize`, :meth:`.Index.factorize`, and :meth:`.ExtensionArray.factorize` (:issue:`47157`)
 -
 

pandas/core/series.py

@@ -1073,21 +1073,14 @@ def __setitem__(self, key, value) -> None:
             # We have a scalar (or for MultiIndex or object-dtype, scalar-like)
             #  key that is not present in self.index.
             if is_integer(key) and self.index.inferred_type != "integer":
-                # positional setter
                 if not self.index._should_fallback_to_positional:
                     # GH#33469
-                    warnings.warn(
-                        "Treating integers as positional in Series.__setitem__ "
-                        "with a Float64Index is deprecated. In a future version, "
-                        "`series[an_int] = val` will insert a new key into the "
-                        "Series. Use `series.iloc[an_int] = val` to treat the "
-                        "key as positional.",
-                        FutureWarning,
-                        stacklevel=find_stack_level(),
-                    )
-                # can't use _mgr.setitem_inplace yet bc could have *both*
-                #  KeyError and then ValueError, xref GH#45070
-                self._set_values(key, value)
+                    self.loc[key] = value
+                else:
+                    # positional setter
+                    # can't use _mgr.setitem_inplace yet bc could have *both*
+                    #  KeyError and then ValueError, xref GH#45070
+                    self._set_values(key, value)
             else:
                 # GH#12862 adding a new key to the Series
                 self.loc[key] = value

pandas/tests/indexing/test_coercion.py

@@ -99,12 +99,9 @@ def _assert_setitem_index_conversion(
     ):
         """test index's coercion triggered by assign key"""
         temp = original_series.copy()
-        warn = None
-        if isinstance(loc_key, int) and temp.index.dtype == np.float64:
-            # GH#33469
-            warn = FutureWarning
-        with tm.assert_produces_warning(warn):
-            temp[loc_key] = 5
+        # GH#33469 pre-2.0 with int loc_key and temp.index.dtype == np.float64
+        #  `temp[loc_key] = 5` treated loc_key as positional
+        temp[loc_key] = 5
         exp = pd.Series([1, 2, 3, 4, 5], index=expected_index)
         tm.assert_series_equal(temp, exp)
         # check dtype explicitly for sure
@@ -144,23 +141,12 @@ def test_setitem_index_int64(self, val, exp_dtype):
         self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)
 
     @pytest.mark.parametrize(
-        "val,exp_dtype", [(5, IndexError), (5.1, np.float64), ("x", object)]
+        "val,exp_dtype", [(5, np.float64), (5.1, np.float64), ("x", object)]
     )
     def test_setitem_index_float64(self, val, exp_dtype, request):
         obj = pd.Series([1, 2, 3, 4], index=[1.1, 2.1, 3.1, 4.1])
         assert obj.index.dtype == np.float64
 
-        if exp_dtype is IndexError:
-            # float + int -> int
-            temp = obj.copy()
-            msg = "index 5 is out of bounds for axis 0 with size 4"
-            with pytest.raises(exp_dtype, match=msg):
-                # GH#33469
-                depr_msg = "Treating integers as positional"
-                with tm.assert_produces_warning(FutureWarning, match=depr_msg):
-                    temp[5] = 5
-            mark = pytest.mark.xfail(reason="TODO_GH12747 The result must be float")
-            request.node.add_marker(mark)
         exp_index = pd.Index([1.1, 2.1, 3.1, 4.1, val])
         self._assert_setitem_index_conversion(obj, val, exp_index, exp_dtype)
 

pandas/tests/series/indexing/test_setitem.py

@@ -1536,41 +1536,37 @@ def test_setitem_positional_float_into_int_coerces():
     tm.assert_series_equal(ser, expected)
 
 
-def test_setitem_int_as_positional_fallback_deprecation():
+def test_setitem_int_not_positional():
     # GH#42215 deprecated falling back to positional on __setitem__ with an
-    #  int not contained in the index
+    #  int not contained in the index; enforced in 2.0
     ser = Series([1, 2, 3, 4], index=[1.1, 2.1, 3.0, 4.1])
     assert not ser.index._should_fallback_to_positional
     # assert not ser.index.astype(object)._should_fallback_to_positional
 
-    with tm.assert_produces_warning(None):
-        # 3.0 is in our index, so future behavior is unchanged
-        ser[3] = 10
+    # 3.0 is in our index, so post-enforcement behavior is unchanged
+    ser[3] = 10
     expected = Series([1, 2, 10, 4], index=ser.index)
     tm.assert_series_equal(ser, expected)
 
-    msg = "Treating integers as positional in Series.__setitem__"
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        with pytest.raises(IndexError, match="index 5 is out of bounds"):
-            ser[5] = 5
-    # Once the deprecation is enforced, we will have
-    #  expected = Series([1, 2, 3, 4, 5], index=[1.1, 2.1, 3.0, 4.1, 5.0])
+    # pre-enforcement `ser[5] = 5` raised IndexError
+    ser[5] = 5
+    expected = Series([1, 2, 10, 4, 5], index=[1.1, 2.1, 3.0, 4.1, 5.0])
+    tm.assert_series_equal(ser, expected)
 
     ii = IntervalIndex.from_breaks(range(10))[::2]
     ser2 = Series(range(len(ii)), index=ii)
-    expected2 = ser2.copy()
-    expected2.iloc[-1] = 9
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        ser2[4] = 9
+    exp_index = ii.astype(object).append(Index([4]))
+    expected2 = Series([0, 1, 2, 3, 4, 9], index=exp_index)
+    # pre-enforcement `ser2[4] = 9` interpreted 4 as positional
+    ser2[4] = 9
     tm.assert_series_equal(ser2, expected2)
 
     mi = MultiIndex.from_product([ser.index, ["A", "B"]])
     ser3 = Series(range(len(mi)), index=mi)
     expected3 = ser3.copy()
-    expected3.iloc[4] = 99
-
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        ser3[4] = 99
+    expected3.loc[4] = 99
+    # pre-enforcement `ser3[4] = 99` interpreted 4 as positional
+    ser3[4] = 99
     tm.assert_series_equal(ser3, expected3)