[pull] main from pydata:main

.pre-commit-config.yaml

@@ -67,14 +67,14 @@ repos:
       - id: sync-mypy-version
         name: sync mypy version
         language: python
-        files: ^\.pre-commit-config\.yaml$
+        files: ^(\.pre-commit-config\.yaml|pixi\.toml|ci/nightly/pixi\.toml)$
         pass_filenames: false
         entry: >-
           python -c "import pathlib, re;
           config = pathlib.Path('.pre-commit-config.yaml').read_text();
           version = re.search(r'mirrors-mypy\s+rev: v?([0-9.]+)', config).group(1);
-          pixi = pathlib.Path('pixi.toml');
-          pixi.write_text(re.sub(r'(?m)^mypy = \"==[0-9.]+\"', f'mypy = \"=={version}\"', pixi.read_text()));
+          [pixi.write_text(re.sub(r'(?m)^mypy = \"==[0-9.]+\"', f'mypy = \"=={version}\"', pixi.read_text()))
+          for pixi in map(pathlib.Path, ['pixi.toml', 'ci/nightly/pixi.toml'])];
           pyproject = pathlib.Path('pyproject.toml');
           pyproject.write_text(re.sub(r'\"mypy==[0-9.]+\"', f'\"mypy=={version}\"', pyproject.read_text()))"
   - repo: https://github.com/citation-file-format/cff-converter-python

ci/nightly/pixi.toml

@@ -80,7 +80,7 @@ cartopy = "*"
 seaborn = "*"
 
 [feature.typing.dependencies]
-mypy = "==1.19.1"
+mypy = "==2.3.1"
 pyright = "*"
 hypothesis = "*"
 lxml = "*"

doc/whats-new.rst

@@ -53,6 +53,13 @@ Deprecations
 Bug Fixes
 ~~~~~~~~~
 
+- ``min`` and ``max`` of object arrays with ``skipna=False`` now return ``NaN``
+  for slices containing missing values, instead of a result that depended on
+  the position of the missing value (:issue:`11501`, :pull:`#11627`).
+  By `Michael Niklas <https://github.com/headtr1ck>`_.
+- Avoid pandas' deprecated ``Series.values`` when creating a
+  :py:class:`~xarray.Variable` from a timezone-aware :py:class:`pandas.Series`
+  (:issue:`11501`, :pull:`#11627`).
 - Fix deadlocks when reading and writing netCDF files with dask at the same
   time. Combined locks now always acquire their locks in the same order, which
   previously depended on memory addresses, and a failed non-blocking acquire,

xarray/core/duck_array_ops.py

@@ -538,6 +538,18 @@ def f(values, axis=None, skipna=None, **kwargs):
 
             nanname = "nan" + name
             func = getattr(nanops, nanname)
+        elif name in ["min", "max"] and dtypes.is_object(values.dtype):
+            # numpy's min/max of object arrays give order-dependent results
+            # when NaN is present, so compute ignoring nulls and then mask
+            # every slice that contains a null
+            from xarray.computation import nanops
+
+            nanfunc = getattr(nanops, "nan" + name)
+
+            def func(values, axis=None, **kwargs):
+                result = nanfunc(values, axis=axis, **kwargs)
+                return where_method(result, ~array_any(isnull(values), axis=axis))
+
         else:
             if name in ["sum", "prod"]:
                 kwargs.pop("min_count", None)

xarray/core/variable.py

@@ -292,6 +292,10 @@ def convert_non_numpy_type(data):
             and not isinstance(data.array, UNSUPPORTED_EXTENSION_ARRAY_TYPES)
         ):
             pandas_data = data.array
+        elif isinstance(data, pd.Series) and isinstance(data.dtype, pd.DatetimeTZDtype):
+            # Series.values is deprecated for timezone-aware data; convert
+            # to UTC datetime64 explicitly instead
+            pandas_data = data.to_numpy(dtype=f"datetime64[{data.dtype.unit}]")  # type: ignore[assignment]
         else:
             pandas_data = data.values  # type: ignore[assignment]
         if isinstance(pandas_data, NON_NUMPY_SUPPORTED_ARRAY_TYPES):

xarray/tests/test_backends.py

@@ -5877,6 +5877,12 @@ def test_roundtrip_string_encoded_characters(self) -> None:
     def test_roundtrip_coordinates_with_space(self) -> None:
         pass
 
+    @pytest.mark.skip(
+        reason="nulls are only replaced when encoding, which does not happen here"
+    )
+    def test_roundtrip_stringdtype_nulls(self) -> None:
+        pass
+
     def test_roundtrip_numpy_datetime_data(self) -> None:
         # Override method in DatasetIOBase - remove not applicable
         # save_kwargs

xarray/tests/test_dataarray.py

@@ -5271,7 +5271,7 @@ def test_min(
         assert_identical(result1, expected1)
 
         result2 = ar.min(skipna=False)
-        if nanindex is not None and ar.dtype.kind != "O":
+        if nanindex is not None:
             expected2 = ar.isel(x=nanindex, drop=True)
         else:
             expected2 = expected1
@@ -5308,7 +5308,7 @@ def test_max(
         assert_identical(result1, expected1)
 
         result2 = ar.max(skipna=False)
-        if nanindex is not None and ar.dtype.kind != "O":
+        if nanindex is not None:
             expected2 = ar.isel(x=nanindex, drop=True)
         else:
             expected2 = expected1
@@ -5820,8 +5820,7 @@ def test_min(
         assert_identical(result2, expected0)  # Default keeps attrs
 
         minindex = [
-            x if y is None or ar.dtype.kind == "O" else y
-            for x, y in zip(minindex, nanindex, strict=True)
+            x if y is None else y for x, y in zip(minindex, nanindex, strict=True)
         ]
         expected2list = [
             ar.isel(y=yi).isel(x=indi, drop=True) for yi, indi in enumerate(minindex)
@@ -5870,8 +5869,7 @@ def test_max(
         assert_identical(result2, expected0)  # Default keeps attrs
 
         maxindex = [
-            x if y is None or ar.dtype.kind == "O" else y
-            for x, y in zip(maxindex, nanindex, strict=True)
+            x if y is None else y for x, y in zip(maxindex, nanindex, strict=True)
         ]
         expected2list = [
             ar.isel(y=yi).isel(x=indi, drop=True) for yi, indi in enumerate(maxindex)

xarray/tests/test_duck_array_ops.py

@@ -578,6 +578,23 @@ def test_empty_axis_dtype():
     assert_identical(ds.sum(dim="time")["var"], ds["var"])
 
 
+@pytest.mark.parametrize("func", ["min", "max"])
+@pytest.mark.parametrize(
+    "values", [[1.0, np.nan, 2.0], [np.nan, 1.0, 2.0], [True, np.nan, False]]
+)
+def test_min_max_object_propagates_nan(func, values) -> None:
+    da = DataArray(np.array(values, dtype=object))
+    actual = getattr(da, func)(skipna=False)
+    assert np.isnan(actual.item())
+
+    da2d = DataArray(np.array([[3, np.nan], [2, 1]], dtype=object), dims=("x", "y"))
+    actual = getattr(da2d, func)("y", skipna=False)
+    expected = DataArray(
+        np.array([np.nan, 2 if func == "max" else 1], dtype=object), dims="x"
+    )
+    assert_identical(actual, expected)
+
+
 def _reduce_params():
     for dtype, use_dask, func, skipna in itertools.product(
         [float, int, np.float32, np.bool_],
@@ -643,7 +660,9 @@ def test_reduce(dim_num, dtype, use_dask, func, skipna, aggdim):
                 assert isinstance(da.data, dask_array_type)
             expected = series_reduce(da, func, skipna=skipna, dim=aggdim, ddof=5)
             assert_allclose(actual, expected, rtol=rtol)
-        else:
+        elif not (da.dtype.kind == "O" and not skipna and func in ["min", "max"]):
+            # pandas < 3.1 does not propagate NaN for object arrays here,
+            # see test_min_max_object_propagates_nan instead
             expected = series_reduce(da, func, skipna=skipna, dim=aggdim)
             assert_allclose(actual, expected, rtol=rtol)
 

xarray/tests/test_plot.py

@@ -1870,10 +1870,12 @@ def test_colors(self) -> None:
         artist = self.darray.plot.contour(
             levels=[-0.5, 0.0, 0.5, 1.0], colors=["k", "r", "w", "b"]
         )
-        assert artist.cmap.colors[:5] == ["k", "r", "w", "b"]  # type: ignore[attr-defined,unused-ignore]
+        cmap = artist.cmap
+        assert isinstance(cmap, mpl.colors.ListedColormap)
+        assert cast(list[str], cmap.colors)[:5] == ["k", "r", "w", "b"]
 
         # the last color is now under "over"
-        assert self._color_as_tuple(artist.cmap.get_over()) == (0.0, 0.0, 1.0)
+        assert self._color_as_tuple(cmap.get_over()) == (0.0, 0.0, 1.0)
 
     def test_colors_np_levels(self) -> None:
         # https://github.com/pydata/xarray/issues/3284
@@ -1882,7 +1884,7 @@ def test_colors_np_levels(self) -> None:
         cmap = artist.cmap
         assert isinstance(cmap, mpl.colors.ListedColormap)
 
-        assert artist.cmap.colors[:5] == ["k", "r", "w", "b"]  # type: ignore[attr-defined,unused-ignore]
+        assert cast(list[str], cmap.colors)[:5] == ["k", "r", "w", "b"]
 
         # the last color is now under "over"
         assert self._color_as_tuple(cmap.get_over()) == (0.0, 0.0, 1.0)

xarray/tests/test_variable.py

@@ -2837,7 +2837,7 @@ def test_tz_datetime(self) -> None:
             warnings.simplefilter("ignore")
             actual2: T_DuckArray = as_compatible_data(series)
 
-        np.testing.assert_array_equal(actual2, np.asarray(series.values))
+        np.testing.assert_array_equal(actual2, series.to_numpy(dtype="datetime64[s]"))
         assert actual2.dtype == np.dtype("datetime64[s]")
 
     def test_full_like(self) -> None: