Allow mean with time dtypes

Closes pydata#5897
Closes pydata#6995

Author: dcherian

xarray/core/_aggregations.py

@@ -468,10 +468,6 @@ def mean(
         :ref:`agg`
             User guide on reduction or aggregation operations.
 
-        Notes
-        -----
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(
@@ -510,7 +506,7 @@ def mean(
             duck_array_ops.mean,
             dim=dim,
             skipna=skipna,
-            numeric_only=True,
+            numeric_only=False,
             keep_attrs=keep_attrs,
             **kwargs,
         )
@@ -1630,10 +1626,6 @@ def mean(
         :ref:`agg`
             User guide on reduction or aggregation operations.
 
-        Notes
-        -----
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(
@@ -2903,8 +2895,6 @@ def mean(
         Pass flox-specific keyword arguments in ``**kwargs``.
         See the `flox documentation <https://flox.readthedocs.io>`_ for more.
 
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(
@@ -2952,7 +2942,7 @@ def mean(
                 func="mean",
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 # fill_value=fill_value,
                 keep_attrs=keep_attrs,
                 **kwargs,
@@ -2962,7 +2952,7 @@ def mean(
                 duck_array_ops.mean,
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 keep_attrs=keep_attrs,
                 **kwargs,
             )
@@ -4391,8 +4381,6 @@ def mean(
         Pass flox-specific keyword arguments in ``**kwargs``.
         See the `flox documentation <https://flox.readthedocs.io>`_ for more.
 
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(
@@ -4440,7 +4428,7 @@ def mean(
                 func="mean",
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 # fill_value=fill_value,
                 keep_attrs=keep_attrs,
                 **kwargs,
@@ -4450,7 +4438,7 @@ def mean(
                 duck_array_ops.mean,
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 keep_attrs=keep_attrs,
                 **kwargs,
             )
@@ -5840,8 +5828,6 @@ def mean(
         Pass flox-specific keyword arguments in ``**kwargs``.
         See the `flox documentation <https://flox.readthedocs.io>`_ for more.
 
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(
@@ -7220,8 +7206,6 @@ def mean(
         Pass flox-specific keyword arguments in ``**kwargs``.
         See the `flox documentation <https://flox.readthedocs.io>`_ for more.
 
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> da = xr.DataArray(

xarray/namedarray/_aggregations.py

@@ -363,10 +363,6 @@ def mean(
         :ref:`agg`
             User guide on reduction or aggregation operations.
 
-        Notes
-        -----
-        Non-numeric variables will be removed prior to reducing.
-
         Examples
         --------
         >>> from xarray.namedarray.core import NamedArray

xarray/tests/test_groupby.py

@@ -29,6 +29,7 @@
     assert_identical,
     create_test_data,
     has_cftime,
+    has_dask,
     has_flox,
     has_pandas_ge_2_2,
     requires_cftime,
@@ -2863,3 +2864,43 @@ def test_multiple_groupers_mixed(use_flox) -> None:
 # 1. lambda x: x
 # 2. grouped-reduce on unique coords is identical to array
 # 3. group_over == groupby-reduce along other dimensions
+
+
+# Put your MCVE code here
+import xarray as xr
+
+
+@pytest.mark.parametrize(
+    "chunk",
+    [
+        pytest.param(
+            True, marks=pytest.mark.skipif(not has_dask, reason="requires dask")
+        ),
+        False,
+    ],
+)
+@pytest.mark.parametrize(
+    "use_cftime",
+    [
+        pytest.param(
+            True, marks=pytest.mark.skipif(not has_cftime, reason="requires cftime")
+        ),
+        False,
+    ],
+)
+def test_datetime_mean(chunk, use_cftime):
+    ds = xr.Dataset(
+        {
+            "var1": (
+                ("time",),
+                xr.date_range(
+                    "2021-10-31", periods=10, freq="D", use_cftime=use_cftime
+                ),
+            ),
+            "var2": (("x",), list(range(10))),
+        }
+    )
+    if chunk:
+        ds = ds.chunk()
+    assert "var1" in ds.groupby("x").mean("time")
+    assert "var1" in ds.mean("x")

xarray/util/generate_aggregations.py

@@ -24,8 +24,8 @@
 
 from __future__ import annotations
 
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Any, Callable
+from collections.abc import Callable, Sequence
+from typing import TYPE_CHECKING, Any
 
 from xarray.core import duck_array_ops
 from xarray.core.options import OPTIONS
@@ -496,7 +496,7 @@ def generate_code(self, method, has_keep_attrs):
     Method("any", bool_reduce=True),
     Method("max", extra_kwargs=(skipna,)),
     Method("min", extra_kwargs=(skipna,)),
-    Method("mean", extra_kwargs=(skipna,), numeric_only=True),
+    Method("mean", extra_kwargs=(skipna,), numeric_only=False),
     Method("prod", extra_kwargs=(skipna, min_count), numeric_only=True),
     Method("sum", extra_kwargs=(skipna, min_count), numeric_only=True),
     Method("std", extra_kwargs=(skipna, ddof), numeric_only=True),