DEPR raise PDEP-6 warning in iadd operation with incompatible dtype

doc/source/whatsnew/v2.2.0.rst

@@ -253,6 +253,7 @@ Other Deprecations
 - Deprecated downcasting behavior in :meth:`Series.where`, :meth:`DataFrame.where`, :meth:`Series.mask`, :meth:`DataFrame.mask`, :meth:`Series.clip`, :meth:`DataFrame.clip`; in a future version these will not infer object-dtype columns to non-object dtype, or all-round floats to integer dtype. Call ``result.infer_objects(copy=False)`` on the result for object inference, or explicitly cast floats to ints. To opt in to the future version, use ``pd.set_option("future.no_silent_downcasting", True)`` (:issue:`53656`)
 - Deprecated including the groups in computations when using :meth:`DataFrameGroupBy.apply` and :meth:`DataFrameGroupBy.resample`; pass ``include_groups=False`` to exclude the groups (:issue:`7155`)
 - Deprecated not passing a tuple to :class:`DataFrameGroupBy.get_group` or :class:`SeriesGroupBy.get_group` when grouping by a length-1 list-like (:issue:`25971`)
+- Deprecated setting item of incompatible dtype in inplace arithmetic operations operating on a whole column (e.g. ``df.loc[:, 'a'] += .1``) (:issue:`39584`)
 - Deprecated string ``AS`` denoting frequency in :class:`YearBegin` and strings ``AS-DEC``, ``AS-JAN``, etc. denoting annual frequencies with various fiscal year starts (:issue:`54275`)
 - Deprecated string ``A`` denoting frequency in :class:`YearEnd` and strings ``A-DEC``, ``A-JAN``, etc. denoting annual frequencies with various fiscal year ends (:issue:`54275`)
 - Deprecated string ``BAS`` denoting frequency in :class:`BYearBegin` and strings ``BAS-DEC``, ``BAS-JAN``, etc. denoting annual frequencies with various fiscal year starts (:issue:`54275`)

pandas/core/frame.py

@@ -7389,7 +7389,7 @@ def value_counts(
         if sort:
             counts = counts.sort_values(ascending=ascending)
         if normalize:
-            counts /= counts.sum()
+            counts = counts / counts.sum()
 
         # Force MultiIndex for a list_like subset with a single column
         if is_list_like(subset) and len(subset) == 1:  # type: ignore[arg-type]

pandas/core/generic.py

@@ -12379,6 +12379,15 @@ def _inplace_method(self, other, op) -> Self:
         Wrap arithmetic method to operate inplace.
         """
         result = op(self, other)
+        if self._typ == "series" and result.dtype != self.dtype:
+            warnings.warn(
+                f"Setting an item of incompatible dtype is deprecated "
+                "and will raise in a future error of pandas. "
+                f"Value '{other}' has dtype incompatible with {self.values.dtype}, "
+                "please explicitly cast to a compatible dtype first.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
 
         if self.ndim == 1 and result._indexed_same(self) and result.dtype == self.dtype:
             # GH#36498 this inplace op can _actually_ be inplace.

pandas/core/groupby/groupby.py

@@ -2831,7 +2831,7 @@ def _value_counts(
                 # GH#43999 - deprecation of observed=False
                 observed=False,
             ).transform("sum")
-            result_series /= indexed_group_size
+            result_series = result_series / indexed_group_size
 
             # Handle groups of non-observed categories
             result_series = result_series.fillna(0.0)

pandas/tests/frame/indexing/test_setitem.py

@@ -1341,3 +1341,12 @@ def test_frame_setitem_empty_dataframe(self):
             index=Index([], dtype="datetime64[ns]", name="date"),
         )
         tm.assert_frame_equal(df, expected)
+
+
+def test_iadd_incompatible_dtype() -> None:
+    # https://github.com/pandas-dev/pandas/issues/39584
+    df = DataFrame({"a": [1, 1, 2], "b": [4, 5, 6]})
+    with tm.assert_produces_warning(FutureWarning, match="incompatible dtype"):
+        df.loc[:, "a"] += 0.1
+    expected = DataFrame({"a": [1.1, 1.1, 2.1], "b": [4, 5, 6]})
+    tm.assert_frame_equal(df, expected)

pandas/tests/frame/methods/test_drop.py

@@ -510,7 +510,7 @@ def test_drop_with_duplicate_columns2(self):
 
     def test_drop_inplace_no_leftover_column_reference(self):
         # GH 13934
-        df = DataFrame({"a": [1, 2, 3]})
+        df = DataFrame({"a": [1.0, 2.0, 3.0]})
         a = df.a
         df.drop(["a"], axis=1, inplace=True)
         tm.assert_index_equal(df.columns, Index([], dtype="object"))

pandas/tests/frame/test_arithmetic.py

@@ -1742,7 +1742,8 @@ def test_inplace_ops_identity(self):
         # dtype change
         s = s_orig.copy()
         s2 = s
-        s += 1.5
+        with tm.assert_produces_warning(FutureWarning, match="incompatible dtype"):
+            s += 1.5
         tm.assert_series_equal(s, s2)
         tm.assert_series_equal(s_orig + 1.5, s)
 
@@ -1767,7 +1768,8 @@ def test_inplace_ops_identity(self):
 
         df = df_orig.copy()
         df2 = df
-        df["A"] += 1.5
+        with tm.assert_produces_warning(FutureWarning, match="incompatible dtype"):
+            df["A"] += 1.5
         expected = DataFrame({"A": arr.copy() + 1.5, "B": "foo"})
         tm.assert_frame_equal(df, expected)
         tm.assert_frame_equal(df2, expected)

pandas/tests/groupby/methods/test_value_counts.py

@@ -397,7 +397,7 @@ def test_compound(
         expected[column] = [education_df[column][row] for row in expected_rows]
     if normalize:
         expected["proportion"] = expected_count
-        expected["proportion"] /= expected_group_size
+        expected["proportion"] = expected["proportion"] / expected_group_size
     else:
         expected["count"] = expected_count
     tm.assert_frame_equal(result, expected)

pandas/tests/series/indexing/test_setitem.py

@@ -1809,3 +1809,12 @@ def test_setitem_empty_mask_dont_upcast_dt64():
     ser.mask(mask, "foo", inplace=True)
     assert ser.dtype == dti.dtype  # no-op -> dont upcast
     tm.assert_series_equal(ser, orig)
+
+
+def test_iadd_incompatible_dtype() -> None:
+    # https://github.com/pandas-dev/pandas/issues/39584
+    ser = Series([1, 2, 3])
+    with tm.assert_produces_warning(FutureWarning, match="incompatible dtype"):
+        ser.loc[:] += 2.2
+    expected = Series([3.2, 4.2, 5.2])
+    tm.assert_series_equal(ser, expected)