REGR: DataFrame.resample fails on a frame with no columns

doc/source/whatsnew/v2.0.1.rst

@@ -15,6 +15,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression for subclassed Series when constructing from a dictionary (:issue:`52445`)
 - Fixed regression in :meth:`DataFrame.pivot` changing :class:`Index` name of input object (:issue:`52629`)
+- Fixed regression in :meth:`DataFrame.resample` raising on a DataFrame with no columns (:issue:`52484`)
 - Fixed regression in :meth:`DataFrame.sort_values` not resetting index when :class:`DataFrame` is already sorted and ``ignore_index=True`` (:issue:`52553`)
 - Fixed regression in :meth:`MultiIndex.isin` raising ``TypeError`` for ``Generator`` (:issue:`52568`)
 - Fixed regression in :meth:`Series.describe` showing ``RuntimeWarning`` for extension dtype :class:`Series` with one element (:issue:`52515`)

pandas/core/resample.py

@@ -483,7 +483,7 @@ def _wrap_result(self, result):
         obj = self.obj
         if (
             isinstance(result, ABCDataFrame)
-            and result.empty
+            and len(result) == 0
             and not isinstance(result.index, PeriodIndex)
         ):
             result = result.set_index(

pandas/tests/resample/test_resample_api.py

@@ -1007,3 +1007,24 @@ def test_series_axis_param_depr():
     )
     with tm.assert_produces_warning(FutureWarning, match=warning_msg):
         test_series.resample("H", axis=0)
+
+
+def test_resample_empty():
+    # GH#52484
+    df = DataFrame(
+        index=pd.to_datetime(
+            ["2018-01-01 00:00:00", "2018-01-01 12:00:00", "2018-01-02 00:00:00"]
+        )
+    )
+    expected = DataFrame(
+        index=pd.to_datetime(
+            [
+                "2018-01-01 00:00:00",
+                "2018-01-01 08:00:00",
+                "2018-01-01 16:00:00",
+                "2018-01-02 00:00:00",
+            ]
+        )
+    )
+    result = df.resample("8H").mean()
+    tm.assert_frame_equal(result, expected)

pandas/tests/resample/test_resampler_grouper.py

@@ -525,7 +525,7 @@ def test_groupby_resample_with_list_of_keys():
 
 
 @pytest.mark.parametrize("keys", [["a"], ["a", "b"]])
-def test_resample_empty_Dataframe(keys):
+def test_resample_no_index(keys):
     # GH 47705
     df = DataFrame([], columns=["a", "b", "date"])
     df["date"] = pd.to_datetime(df["date"])
@@ -542,6 +542,66 @@ def test_resample_empty_Dataframe(keys):
     tm.assert_frame_equal(result, expected)
 
 
+def test_resample_no_columns():
+    # GH#52484
+    df = DataFrame(
+        index=Index(
+            pd.to_datetime(
+                ["2018-01-01 00:00:00", "2018-01-01 12:00:00", "2018-01-02 00:00:00"]
+            ),
+            name="date",
+        )
+    )
+    result = df.groupby([0, 0, 1]).resample(rule=pd.to_timedelta("06:00:00")).mean()
+    index = pd.to_datetime(
+        [
+            "2018-01-01 00:00:00",
+            "2018-01-01 06:00:00",
+            "2018-01-01 12:00:00",
+            "2018-01-02 00:00:00",
+        ]
+    )
+    expected = DataFrame(
+        index=pd.MultiIndex(
+            levels=[[0, 1], index],
+            codes=[[0, 0, 0, 1], [0, 1, 2, 3]],
+            names=[None, "date"],
+        )
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+def test_resample_one_column():
+    # GH#52484
+    df = DataFrame(
+        data=[4, 5, 6],
+        index=Index(
+            pd.to_datetime(
+                ["2018-01-01 00:00:00", "2018-01-01 12:00:00", "2018-01-02 00:00:00"]
+            ),
+            name="date",
+        ),
+    )
+    result = df.groupby([0, 0, 1]).resample(rule=pd.to_timedelta("06:00:00")).mean()
+    index = pd.to_datetime(
+        [
+            "2018-01-01 00:00:00",
+            "2018-01-01 06:00:00",
+            "2018-01-01 12:00:00",
+            "2018-01-02 00:00:00",
+        ]
+    )
+    expected = DataFrame(
+        data=[4.0, np.nan, 5.0, 6.0],
+        index=pd.MultiIndex(
+            levels=[[0, 1], index],
+            codes=[[0, 0, 0, 1], [0, 1, 2, 3]],
+            names=[None, "date"],
+        ),
+    )
+    tm.assert_frame_equal(result, expected)
+
+
 def test_groupby_resample_size_all_index_same():
     # GH 46826
     df = DataFrame(