BUG: #57775 Fix groupby apply in case func returns None for all groups

doc/source/whatsnew/v2.2.2.rst

@@ -21,7 +21,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
--
+- :meth:`DataFrameGroupBy.apply` was returning a completely empty DataFrame when all return values of ``func`` were ``None`` instead of returning an empty DataFrame with the original columns and dtypes. (:issue:`57775`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_222.other:

pandas/core/groupby/generic.py

@@ -1642,8 +1642,11 @@ def _wrap_applied_output(
         first_not_none = next(com.not_none(*values), None)
 
         if first_not_none is None:
-            # GH9684 - All values are None, return an empty frame.
-            return self.obj._constructor()
+            # GH9684 - All values are None, return an empty frame
+            # GH57775 - Ensure that columns and dtypes from original frame are kept.
+            result = self.obj._constructor(columns=data.columns)
+            result = result.astype(data.dtypes)
+            return result
         elif isinstance(first_not_none, DataFrame):
             return self._concat_objects(
                 values,

pandas/core/groupby/groupby.py

@@ -1572,6 +1572,13 @@ def apply(self, func, *args, include_groups: bool = True, **kwargs) -> NDFrameT:
         behavior or errors and are not supported. See :ref:`gotchas.udf-mutation`
         for more details.
 
+        Groups for which ``func`` returns ``None`` will be filtered from the result.
+
+        .. versionchanged:: 2.2.2
+
+            In case all groups are filtered from the result, an empty DataFrame
+            with the columns and dtypes of the original dataframe will be returned.
+
         Examples
         --------
         >>> df = pd.DataFrame({"A": "a a b".split(), "B": [1, 2, 3], "C": [4, 6, 5]})
@@ -1636,6 +1643,14 @@ def apply(self, func, *args, include_groups: bool = True, **kwargs) -> NDFrameT:
         a    5
         b    2
         dtype: int64
+
+        Example 4: The function passed to ``apply`` returns ``None`` for one of the
+        group. This group is filtered from the result:
+
+        >>> g1.apply(lambda x: None if x.iloc[0, 0] == 3 else x, include_groups=False)
+           B  C
+        0  1  4
+        1  2  6
         """
         if isinstance(func, str):
             if hasattr(self, func):

pandas/tests/groupby/test_apply.py

@@ -838,7 +838,8 @@ def test_func(x):
     msg = "DataFrameGroupBy.apply operated on the grouping columns"
     with tm.assert_produces_warning(DeprecationWarning, match=msg):
         result = test_df.groupby("groups").apply(test_func)
-    expected = DataFrame()
+    expected = DataFrame(columns=test_df.columns)
+    expected = expected.astype(test_df.dtypes)
     tm.assert_frame_equal(result, expected)