Allow mean with time dtypes

xarray/core/_aggregations.py

@@ -1776,10 +1776,6 @@ 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(
@@ -1818,7 +1814,7 @@ def mean(
             duck_array_ops.mean,
             dim=dim,
             skipna=skipna,
-            numeric_only=True,
+            numeric_only=False,
             keep_attrs=keep_attrs,
             **kwargs,
         )
@@ -2948,10 +2944,6 @@ 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(
@@ -4231,8 +4223,6 @@ 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(
@@ -4280,7 +4270,7 @@ def mean(
                 func="mean",
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 # fill_value=fill_value,
                 keep_attrs=keep_attrs,
                 **kwargs,
@@ -4290,7 +4280,7 @@ def mean(
                 duck_array_ops.mean,
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 keep_attrs=keep_attrs,
                 **kwargs,
             )
@@ -5729,8 +5719,6 @@ 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(
@@ -5778,7 +5766,7 @@ def mean(
                 func="mean",
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 # fill_value=fill_value,
                 keep_attrs=keep_attrs,
                 **kwargs,
@@ -5788,7 +5776,7 @@ def mean(
                 duck_array_ops.mean,
                 dim=dim,
                 skipna=skipna,
-                numeric_only=True,
+                numeric_only=False,
                 keep_attrs=keep_attrs,
                 **kwargs,
             )
@@ -7188,8 +7176,6 @@ 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(
@@ -8578,8 +8564,6 @@ 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

@@ -352,10 +352,6 @@ 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

@@ -905,7 +905,7 @@
     if letters_as_coord:
         data = data.set_coords("letters")
 
     expected = data.mean("y")
     expected["yonly"] = expected["yonly"].variable.set_dims({"x": 3})
     gb = data.groupby(by_func("x"))
     with xr.set_options(use_flox=use_flox):
@@ -3292,6 +3292,33 @@
     ds.groupby_bins("x", bins=[1, 2, 3], eagerly_compute_group=False)
 
 
+@pytest.mark.parametrize(
+    "chunk",
+    [
+        pytest.param(
+            True, marks=pytest.mark.skipif(not has_dask, reason="requires dask")
+        ),
+        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")
+
+
 # TODO: Possible property tests to add to this module
 # 1. lambda x: x
 # 2. grouped-reduce on unique coords is identical to array

xarray/util/generate_aggregations.py

@@ -515,7 +515,7 @@ 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),