clean commit

Author: szczekulskij

pandas/core/apply.py

@@ -406,8 +406,6 @@ def agg_dict_like(self) -> DataFrame | Series:
 
         arg = self.normalize_dictlike_arg("agg", selected_obj, arg)
 
-        print("type self:", type(self))
-        print("type obj:", type(obj))
         is_groupby = isinstance(obj, (DataFrameGroupBy, SeriesGroupBy))
         context_manager: ContextManager
         if is_groupby:

pandas/core/groupby/generic.py

@@ -361,7 +361,7 @@ def _wrap_applied_output(
         values: list[Any],
         not_indexed_same: bool = False,
         is_transform: bool = False,
-        edge_case_jan: bool = True,
+        skip_as_index: bool = False,
     ) -> DataFrame | Series:
         """
         Wrap the output of SeriesGroupBy.apply into the expected result.
@@ -411,13 +411,9 @@ def _wrap_applied_output(
                 not_indexed_same=not_indexed_same,
                 is_transform=is_transform,
             )
-            print("yoooohohoho")
-            print(type(self))
-            print(type(result))
-
             if isinstance(result, Series):
                 result.name = self.obj.name
-            if not self.as_index and not_indexed_same and edge_case_jan:
+            if not self.as_index and not_indexed_same and not skip_as_index:
                 result = self._insert_inaxis_grouper(result)
                 result.index = default_index(len(result))
             return result
@@ -1448,7 +1444,7 @@ def _wrap_applied_output(
         values: list,
         not_indexed_same: bool = False,
         is_transform: bool = False,
-        edge_case_jan: bool = False,
+        skip_as_index: bool = False,
     ):
         if len(values) == 0:
             if is_transform:
@@ -1513,7 +1509,7 @@ def _wrap_applied_output_series(
         first_not_none,
         key_index: Index | None,
         is_transform: bool,
-        edge_case_jan: bool = False,
+        skip_as_index: bool = False,
     ) -> DataFrame | Series:
         kwargs = first_not_none._construct_axes_dict()
         backup = Series(**kwargs)

pandas/core/groupby/groupby.py

@@ -1308,7 +1308,7 @@ def _wrap_applied_output(
         values: list,
         not_indexed_same: bool = False,
         is_transform: bool = False,
-        edge_case_jan: bool = True,
+        skip_as_index: bool = True,
     ):
         raise AbstractMethodError(self)
 
@@ -1455,7 +1455,7 @@ def _aggregate_with_numba(self, func, *args, engine_kwargs=None, **kwargs):
             input="dataframe", examples=_apply_docs["dataframe_examples"]
         )
     )
-    def apply(self, func, edge_case_jan=False, *args, **kwargs) -> NDFrameT:
+    def apply(self, func, skip_as_index=False, *args, **kwargs) -> NDFrameT:
         func = com.is_builtin_func(func)
 
         if isinstance(func, str):
@@ -1488,7 +1488,7 @@ def f(g):
         with option_context("mode.chained_assignment", None):
             try:
                 result = self._python_apply_general(
-                    f, self._selected_obj, edge_case_jan=edge_case_jan
+                    f, self._selected_obj, skip_as_index=skip_as_index
                 )
                 if (
                     not isinstance(self.obj, Series)
@@ -1521,7 +1521,7 @@ def _python_apply_general(
         not_indexed_same: bool | None = None,
         is_transform: bool = False,
         is_agg: bool = False,
-        edge_case_jan: bool = False,
+        skip_as_index: bool = False,
     ) -> NDFrameT:
         """
         Apply function f in python space
@@ -1554,7 +1554,7 @@ def _python_apply_general(
             not_indexed_same = mutated
 
         return self._wrap_applied_output(
-            data, values, not_indexed_same, is_transform, edge_case_jan
+            data, values, not_indexed_same, is_transform, skip_as_index
         )
 
     @final

pandas/core/resample.py

@@ -1370,7 +1370,7 @@ def func(x):
             target_category=FutureWarning,
             new_message=msg,
         ):
-            result = self._groupby.apply(func, edge_case_jan=False)
+            result = self._groupby.apply(func, skip_as_index=False)
         return self._wrap_result(result)
 
     _upsample = _apply