ENH: Add numeric_only to resampler methods

doc/source/whatsnew/v1.5.0.rst

@@ -96,6 +96,7 @@ Other enhancements
 - :meth:`pd.concat` now raises when ``levels`` contains duplicate values (:issue:`46653`)
 - Added ``numeric_only`` argument to :meth:`DataFrame.corr`, :meth:`DataFrame.corrwith`, and :meth:`DataFrame.cov` (:issue:`46560`)
 - A :class:`errors.PerformanceWarning` is now thrown when using ``string[pyarrow]`` dtype with methods that don't dispatch to ``pyarrow.compute`` methods (:issue:`42613`)
+- Added ``numeric_only`` argument to :meth:`Resampler.sum`, :meth:`Resampler.prod`, :meth:`Resampler.min`, :meth:`Resampler.max`, :meth:`Resampler.first`, and :meth:`Resampler.last` (:issue:`46442`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_150.notable_bug_fixes:

pandas/core/resample.py

@@ -1027,9 +1027,22 @@ def quantile(self, q=0.5, **kwargs):
 # downsample methods
 for method in ["sum", "prod", "min", "max", "first", "last"]:
 
-    def f(self, _method=method, min_count=0, *args, **kwargs):
+    def f(
+        self,
+        _method: str = method,
+        numeric_only: bool | lib.NoDefault = lib.no_default,
+        min_count: int = 0,
+        *args,
+        **kwargs,
+    ):
+        if numeric_only is lib.no_default:
+            if (self.obj.ndim == 1) or (_method != "sum"):
+                # For SeriesGroupBy, set the default to be False.
+                # For DataFrameGroupBy, set it to be False for methods other than `sum`.
+                numeric_only = False
+
         nv.validate_resampler_func(_method, args, kwargs)
-        return self._downsample(_method, min_count=min_count)
+        return self._downsample(_method, numeric_only=numeric_only, min_count=min_count)
 
     f.__doc__ = getattr(GroupBy, method).__doc__
     setattr(Resampler, method, f)

pandas/tests/resample/test_resample_api.py

@@ -771,3 +771,58 @@ def test_end_and_end_day_origin(
     )
 
     tm.assert_series_equal(res, expected)
+
+
+@pytest.mark.parametrize("numeric_only", [True, False])
+def test_downsample_method(numeric_only):
+    # test if `numeric_only` behave as expected for Resampler downsample methods.
+
+    index = date_range("2018-01-01", periods=2, freq="D")
+    expected_index = date_range("2018-12-31", periods=1, freq="Y")
+    df = DataFrame({"cat": ["cat_1", "cat_2"], "num": [5, 20]}, index=index)
+    resampled = df.resample("Y")
+
+    # test Resampler.sum
+    result = resampled.sum(numeric_only=numeric_only)
+    if numeric_only:
+        expected = DataFrame({"num": [25]}, index=expected_index)
+    else:
+        expected = DataFrame({"cat": ["cat_1cat_2"], "num": [25]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)
+
+    # test Resampler.prod
+    result = resampled.prod(numeric_only=numeric_only)
+    expected = DataFrame({"num": [100]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)
+
+    # test Resampler.min
+    result = resampled.min(numeric_only=numeric_only)
+    if numeric_only:
+        expected = DataFrame({"num": [5]}, index=expected_index)
+    else:
+        expected = DataFrame({"cat": ["cat_1"], "num": [5]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)
+
+    # test Resampler.max
+    result = resampled.max(numeric_only=numeric_only)
+    if numeric_only:
+        expected = DataFrame({"num": [20]}, index=expected_index)
+    else:
+        expected = DataFrame({"cat": ["cat_2"], "num": [20]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)
+
+    # test Resampler.first
+    result = resampled.first(numeric_only=numeric_only)
+    if numeric_only:
+        expected = DataFrame({"num": [5]}, index=expected_index)
+    else:
+        expected = DataFrame({"cat": ["cat_1"], "num": [5]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)
+
+    # test Resampler.last
+    result = resampled.last(numeric_only=numeric_only)
+    if numeric_only:
+        expected = DataFrame({"num": [20]}, index=expected_index)
+    else:
+        expected = DataFrame({"cat": ["cat_2"], "num": [20]}, index=expected_index)
+    tm.assert_frame_equal(result, expected)