BUG: Allow named aggregation with Resampler.agg

doc/source/whatsnew/v1.4.0.rst

@@ -329,6 +329,8 @@ Groupby/resample/rolling
 - Bug in :meth:`SeriesGroupBy.nlargest` and :meth:`SeriesGroupBy.nsmallest` would have an inconsistent index when the input Series was sorted and ``n`` was greater than or equal to all group sizes (:issue:`15272`, :issue:`16345`, :issue:`29129`)
 - Bug in :meth:`pandas.DataFrame.ewm`, where non-float64 dtypes were silently failing (:issue:`42452`)
 - Bug in :meth:`pandas.DataFrame.rolling` operation along rows (``axis=1``) incorrectly omits columns containing ``float16`` and ``float32`` (:issue:`41779`)
+- Bug in :meth:`Resampler.aggregate` did not allow the use of Named Aggregation (:issue:`32803`)
+-
 
 Reshaping
 ^^^^^^^^^

pandas/core/resample.py

@@ -316,6 +316,12 @@ def pipe(
     2013-01-01 00:00:00  2.121320      3
     2013-01-01 00:00:02  4.949747      7
     2013-01-01 00:00:04       NaN      5
+
+    >>> r.agg(average="mean", total="sum")
+                             average  total
+    2013-01-01 00:00:00      1.5      3
+    2013-01-01 00:00:02      3.5      7
+    2013-01-01 00:00:04      5.0      5
     """
     )
 
@@ -326,7 +332,7 @@ def pipe(
         klass="DataFrame",
         axis="",
     )
-    def aggregate(self, func, *args, **kwargs):
+    def aggregate(self, func=None, *args, **kwargs):
 
         result = ResamplerWindowApply(self, func, args=args, kwargs=kwargs).agg()
         if result is None:

pandas/tests/resample/test_resample_api.py

@@ -6,6 +6,7 @@
 import pandas as pd
 from pandas import (
     DataFrame,
+    NamedAgg,
     Series,
 )
 import pandas._testing as tm
@@ -362,6 +363,12 @@ def test_agg():
         result = t.aggregate({"A": np.mean, "B": np.std})
         tm.assert_frame_equal(result, expected, check_like=True)
 
+        result = t.aggregate(A=("A", np.mean), B=("B", np.std))
+        tm.assert_frame_equal(result, expected, check_like=True)
+
+        result = t.aggregate(A=NamedAgg("A", np.mean), B=NamedAgg("B", np.std))
+        tm.assert_frame_equal(result, expected, check_like=True)
+
     expected = pd.concat([a_mean, a_std], axis=1)
     expected.columns = pd.MultiIndex.from_tuples([("A", "mean"), ("A", "std")])
     for t in cases:
@@ -372,7 +379,10 @@ def test_agg():
     expected.columns = ["mean", "sum"]
     for t in cases:
         result = t["A"].aggregate(["mean", "sum"])
-    tm.assert_frame_equal(result, expected)
+        tm.assert_frame_equal(result, expected)
+
+        result = t["A"].aggregate(mean="mean", sum="sum")
+        tm.assert_frame_equal(result, expected)
 
     msg = "nested renamer is not supported"
     for t in cases:
@@ -439,6 +449,14 @@ def test_agg_misc():
         expected = pd.concat([r["A"].sum(), rcustom], axis=1)
         tm.assert_frame_equal(result, expected, check_like=True)
 
+        result = t.agg(A=("A", np.sum), B=("B", lambda x: np.std(x, ddof=1)))
+        tm.assert_frame_equal(result, expected, check_like=True)
+
+        result = t.agg(
+            A=NamedAgg("A", np.sum), B=NamedAgg("B", lambda x: np.std(x, ddof=1))
+        )
+        tm.assert_frame_equal(result, expected, check_like=True)
+
     # agg with renamers
     expected = pd.concat(
         [t["A"].sum(), t["B"].sum(), t["A"].mean(), t["B"].mean()], axis=1
@@ -452,6 +470,14 @@ def test_agg_misc():
         with pytest.raises(KeyError, match=msg):
             t[["A", "B"]].agg({"result1": np.sum, "result2": np.mean})
 
+        with pytest.raises(KeyError, match=msg):
+            t[["A", "B"]].agg(A=("result1", np.sum), B=("result2", np.mean))
+
+        with pytest.raises(KeyError, match=msg):
+            t[["A", "B"]].agg(
+                A=NamedAgg("result1", np.sum), B=NamedAgg("result2", np.mean)
+            )
+
     # agg with different hows
     expected = pd.concat(
         [t["A"].sum(), t["A"].std(), t["B"].mean(), t["B"].std()], axis=1