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

doc/source/whatsnew/v3.0.0.rst

@@ -284,6 +284,7 @@ Bug fixes
 - Fixed bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
 - Fixed bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames. (:issue:`16098`)
 - Fixed bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
+- Fixed bug in :meth:`DataFrameGroupBy.apply` that 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`)
 - Fixed bug in :meth:`Series.diff` allowing non-integer values for the ``periods`` argument. (:issue:`56607`)
 - Fixed bug in :meth:`Series.rank` that doesn't preserve missing values for nullable integers when ``na_option='keep'``. (:issue:`56976`)
 

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

@@ -1636,6 +1636,14 @@ 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)