Fix groupby-resample KeyError when resampling on Index and giving explicit list of columns.

doc/source/whatsnew/v2.0.0.rst

@@ -1096,6 +1096,7 @@ Groupby/resample/rolling
 - Bug in :meth:`.DataFrameGroupBy.transform` and :meth:`.SeriesGroupBy.transform` would raise incorrectly when grouper had ``axis=1`` for ``"idxmin"`` and ``"idxmax"`` arguments (:issue:`45986`)
 - Bug in :class:`.DataFrameGroupBy` would raise when used with an empty DataFrame, categorical grouper, and ``dropna=False`` (:issue:`50634`)
 - Bug in :meth:`.SeriesGroupBy.value_counts` did not respect ``sort=False`` (:issue:`50482`)
+- Bug in :meth:`.DataFrameGroupBy.resample` raises ``KeyError`` when getting the result from a key list when resampling on time index (:issue:`50840`)
 -
 
 Reshaping

pandas/core/resample.py

@@ -1202,7 +1202,7 @@ def _gotitem(self, key, ndim, subset=None):
 
         # Try to select from a DataFrame, falling back to a Series
         try:
-            if isinstance(key, list) and self.key not in key:
+            if isinstance(key, list) and self.key not in key and self.key is not None:
                 key.append(self.key)
             groupby = self._groupby[key]
         except IndexError:

pandas/tests/resample/test_resampler_grouper.py

@@ -536,3 +536,82 @@ def test_groupby_resample_size_all_index_same():
         ),
     )
     tm.assert_series_equal(result, expected)
+
+
+def test_groupby_resample_on_index_with_list_of_keys():
+    # GH 50840
+    df = DataFrame(
+        data={
+            "group": [0, 0, 0, 0, 1, 1, 1, 1],
+            "val": [3, 1, 4, 1, 5, 9, 2, 6],
+        },
+        index=Series(
+            date_range(start="2016-01-01", periods=8),
+            name="date",
+        ),
+    )
+    result = df.groupby("group").resample("2D")[["val"]].mean()
+    expected = DataFrame(
+        data={
+            "val": [2.0, 2.5, 7.0, 4.0],
+        },
+        index=Index(
+            data=[
+                (0, Timestamp("2016-01-01")),
+                (0, Timestamp("2016-01-03")),
+                (1, Timestamp("2016-01-05")),
+                (1, Timestamp("2016-01-07")),
+            ],
+            name=("group", "date"),
+        ),
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_resample_on_index_with_list_of_keys_multi_columns():
+    # GH 50876
+    df = DataFrame(
+        data={
+            "group": [0, 0, 0, 0, 1, 1, 1, 1],
+            "first_val": [3, 1, 4, 1, 5, 9, 2, 6],
+            "second_val": [2, 7, 1, 8, 2, 8, 1, 8],
+            "third_val": [1, 4, 1, 4, 2, 1, 3, 5],
+        },
+        index=Series(
+            date_range(start="2016-01-01", periods=8),
+            name="date",
+        ),
+    )
+    result = df.groupby("group").resample("2D")[["first_val", "second_val"]].mean()
+    expected = DataFrame(
+        data={
+            "first_val": [2.0, 2.5, 7.0, 4.0],
+            "second_val": [4.5, 4.5, 5.0, 4.5],
+        },
+        index=Index(
+            data=[
+                (0, Timestamp("2016-01-01")),
+                (0, Timestamp("2016-01-03")),
+                (1, Timestamp("2016-01-05")),
+                (1, Timestamp("2016-01-07")),
+            ],
+            name=("group", "date"),
+        ),
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_resample_on_index_with_list_of_keys_missing_column():
+    # GH 50876
+    df = DataFrame(
+        data={
+            "group": [0, 0, 0, 0, 1, 1, 1, 1],
+            "val": [3, 1, 4, 1, 5, 9, 2, 6],
+        },
+        index=Series(
+            date_range(start="2016-01-01", periods=8),
+            name="date",
+        ),
+    )
+    with pytest.raises(KeyError, match="Columns not found"):
+        df.groupby("group").resample("2D")[["val_not_in_dataframe"]].mean()