ENH: Accept no fields for groupby by

doc/source/whatsnew/v3.0.0.rst

@@ -56,6 +56,7 @@ Other enhancements
 - :meth:`DataFrame.cummin`, :meth:`DataFrame.cummax`, :meth:`DataFrame.cumprod` and :meth:`DataFrame.cumsum` methods now have a ``numeric_only`` parameter (:issue:`53072`)
 - :meth:`DataFrame.ewm` now allows ``adjust=False`` when ``times`` is provided (:issue:`54328`)
 - :meth:`DataFrame.fillna` and :meth:`Series.fillna` can now accept ``value=None``; for non-object dtype the corresponding NA value will be used (:issue:`57723`)
+- :meth:`DataFrame.groupby` now accepts no fields for ``groupby`` by in :meth:`DataFrame.groupby` (:issue:`61160`)
 - :meth:`DataFrame.pivot_table` and :func:`pivot_table` now allow the passing of keyword arguments to ``aggfunc`` through ``**kwargs`` (:issue:`57884`)
 - :meth:`DataFrame.to_json` now encodes ``Decimal`` as strings instead of floats (:issue:`60698`)
 - :meth:`Series.cummin` and :meth:`Series.cummax` now supports :class:`CategoricalDtype` (:issue:`52335`)

pandas/core/frame.py

@@ -9153,8 +9153,8 @@ def groupby(
     ) -> DataFrameGroupBy:
         from pandas.core.groupby.generic import DataFrameGroupBy
 
-        if level is None and by is None:
-            raise TypeError("You have to supply one of 'by' and 'level'")
+        if level is None and (by is None or by == []):
+            by = Series(0, index=self.index)
 
         return DataFrameGroupBy(
             obj=self,

pandas/core/series.py

@@ -1973,8 +1973,8 @@ def groupby(
     ) -> SeriesGroupBy:
         from pandas.core.groupby.generic import SeriesGroupBy
 
-        if level is None and by is None:
-            raise TypeError("You have to supply one of 'by' and 'level'")
+        if level is None and (by is None or by == []):
+            by = Series(0, index=self.index)
         if not as_index:
             raise TypeError("as_index=False only valid with DataFrame")
 

pandas/tests/groupby/test_grouping.py

@@ -695,17 +695,45 @@ def test_groupby_level_with_nas(self, sort):
         expected = Series([6.0, 18.0], index=[0.0, 1.0])
         tm.assert_series_equal(result, expected)
 
+    def test_groupby_without_by(self):
+        # GH 61160
+        df = DataFrame({"A": [1, 2, 3, 4], "B": [10, 20, 30, 40]})
+
+        # Test basic aggregation with no fields
+        result = df.groupby().sum()
+        expected = df.sum().to_frame().T
+        tm.assert_frame_equal(result, expected)
+
+        # Test with multiple aggregations
+        result = df.groupby().agg(["sum", "mean"])
+        expected = df.agg(["sum", "mean"])
+        tm.assert_frame_equal(result, expected)
+
+        # Test Series.groupby() without any fields
+        s = Series([1, 2, 3, 4])
+        result = s.groupby().sum()
+        expected = Series([10])  # Sum of the values
+        tm.assert_series_equal(result, expected)
+
+        # Test with conditional logic - should work with None/empty list
+        groupby_fields = None
+        result = df.groupby(groupby_fields).sum()
+        expected = df.sum().to_frame().T
+        tm.assert_frame_equal(result, expected)
+
+        result = df.groupby([]).sum()
+        tm.assert_frame_equal(result, expected)
+
     def test_groupby_args(self, multiindex_dataframe_random_data):
         # PR8618 and issue 8015
         frame = multiindex_dataframe_random_data
 
-        msg = "You have to supply one of 'by' and 'level'"
-        with pytest.raises(TypeError, match=msg):
-            frame.groupby()
+        result = frame.groupby().sum()
+        expected = frame.sum().to_frame().T
+        tm.assert_frame_equal(result, expected)
 
-        msg = "You have to supply one of 'by' and 'level'"
-        with pytest.raises(TypeError, match=msg):
-            frame.groupby(by=None, level=None)
+        result = frame.groupby(by=None, level=None).sum()
+        tm.assert_frame_equal(result, expected)
 
     @pytest.mark.parametrize(
         "sort,labels",