ENH: Allow empty groupby

doc/source/whatsnew/v2.2.0.rst

@@ -16,7 +16,7 @@ Enhancements
 
 .. _whatsnew_220.enhancements.enhancement1:
 
-enhancement1
+:class:`GroupBy` now accepts an empty list of ``keys`` and applies any aggregation over all the data (:issue:`35366`)
 ^^^^^^^^^^^^
 
 .. _whatsnew_220.enhancements.enhancement2:

pandas/core/groupby/groupby.py

@@ -1289,6 +1289,10 @@ def __init__(
         dropna: bool = True,
     ) -> None:
         self._selection = selection
+        # to resolve case when passed empty list
+        # didn't change self.keys directly to avoid side effects
+        # e.g. the use of get_grouper
+        keys = [np.int64(0)] * len(obj) if (iter(keys) and len(keys) == 0) else keys
 
         assert isinstance(obj, NDFrame), type(obj)
 

pandas/tests/groupby/test_groupby.py

@@ -33,6 +33,62 @@
 pytestmark = pytest.mark.filterwarnings("ignore:Mean of empty slice:RuntimeWarning")
 
 
+def test_groupby_empty_list_keys():
+    # sample case of a series
+    s = Series([1, 2, 3])
+    # result = s.groupby([]).agg("min")
+    result = s.groupby([]).agg("min")
+    expected = Series([1])
+    tm.assert_series_equal(result, expected)
+    # sample case one column
+    df = DataFrame(
+        {
+            "group": ["A", "B", "A"],
+            "col": np.arange(3),
+        }
+    )
+    result_df = df.groupby([]).agg(col_min=("col", "min"))
+    expected_df = DataFrame([{"col_min": 0}])
+    tm.assert_frame_equal(result_df, expected_df)
+
+    # two columns in a datafram with other columns
+    df = DataFrame(
+        {
+            "group": ["A", "B", "A"],
+            "col1": np.arange(3),
+            "col2": np.arange(3, 6),
+            "col3": np.arange(6, 9),
+        }
+    )
+    result_df = df.groupby([]).agg(
+        col1_min=("col1", "min"),
+        col2_min=("col2", "sum"),
+    )
+    expected_df = DataFrame(
+        [{"col1_min": 0, "col2_min": 12}],
+    )
+    tm.assert_frame_equal(result_df, expected_df)
+
+    # std
+    result_df = df.groupby([]).agg(
+        col1_std=("col1", "std"),
+    )
+    expected_df = DataFrame(
+        [{"col1_std": 1.0}],
+    )
+    tm.assert_frame_equal(result_df, expected_df)
+
+    # different type of iterables
+    for key_iter in [np.array([]), (), set()]:
+        result_df = df.groupby(key_iter).agg(
+            col1_std=("col1", "std"),
+        )
+        expected_df = DataFrame(
+            [{"col1_std": 1.0}],
+        )
+        tm.assert_frame_equal(result_df, expected_df)
+
+
 def test_repr():
     # GH18203
     result = repr(Grouper(key="A", level="B"))

pandas/tests/groupby/test_grouping.py

@@ -393,11 +393,6 @@ def test_grouper_getting_correct_binner(self):
     def test_grouper_iter(self, df):
         assert sorted(df.groupby("A").grouper) == ["bar", "foo"]
 
-    def test_empty_groups(self, df):
-        # see gh-1048
-        with pytest.raises(ValueError, match="No group keys passed!"):
-            df.groupby([])
-
     def test_groupby_grouper(self, df):
         grouped = df.groupby("A")