BUG/REF: Refactor BaseWindowIndex so groupby.apply has a consistent index output (pandas-dev#39765)

* Remove _groupby object from class

* Add test that groupby apply is not affected

* Remove unnecessary groupby subclasses

* Supress private variables in repr

* Don't have window classes accept kwargs

* Add whatsnew

* Remove unused constructor

* Just user the grouper

* Make expected index instead

Co-authored-by: Jeff Reback <[email protected]>

Author: mroeschke

doc/source/whatsnew/v1.3.0.rst

@@ -443,6 +443,7 @@ Groupby/resample/rolling
 - Bug in :meth:`.GroupBy.mean`, :meth:`.GroupBy.median` and :meth:`DataFrame.pivot_table` not propagating metadata (:issue:`28283`)
 - Bug in :meth:`Series.rolling` and :meth:`DataFrame.rolling` not calculating window bounds correctly when window is an offset and dates are in descending order (:issue:`40002`)
 - Bug in :class:`SeriesGroupBy` and :class:`DataFrameGroupBy` on an empty ``Series`` or ``DataFrame`` would lose index, columns, and/or data types when directly using the methods ``idxmax``, ``idxmin``, ``mad``, ``min``, ``max``, ``sum``, ``prod``, and ``skew`` or using them through ``apply``, ``aggregate``, or ``resample`` (:issue:`26411`)
+- Bug in :meth:`DataFrameGroupBy.apply` where a :class:`MultiIndex` would be created instead of an :class:`Index` if a :class:`:meth:`core.window.rolling.RollingGroupby` object was created (:issue:`39732`)
 - Bug in :meth:`DataFrameGroupBy.sample` where error was raised when ``weights`` was specified and the index was an :class:`Int64Index` (:issue:`39927`)
 - Bug in :meth:`DataFrameGroupBy.aggregate` and :meth:`.Resampler.aggregate` would sometimes raise ``SpecificationError`` when passed a dictionary and columns were missing; will now always raise a ``KeyError`` instead (:issue:`40004`)
 -

pandas/core/groupby/base.py

@@ -5,7 +5,6 @@
 """
 import collections
 from typing import List
-import warnings
 
 from pandas._typing import final
 
@@ -31,10 +30,7 @@ def _shallow_copy(self, obj, **kwargs):
             obj = obj.obj
         for attr in self._attributes:
             if attr not in kwargs:
-                # TODO: Remove once win_type deprecation is enforced
-                with warnings.catch_warnings():
-                    warnings.filterwarnings("ignore", "win_type", FutureWarning)
-                    kwargs[attr] = getattr(self, attr)
+                kwargs[attr] = getattr(self, attr)
         return self._constructor(obj, **kwargs)
 
 
@@ -65,10 +61,7 @@ def _gotitem(self, key, ndim, subset=None):
 
         # we need to make a shallow copy of ourselves
         # with the same groupby
-        # TODO: Remove once win_type deprecation is enforced
-        with warnings.catch_warnings():
-            warnings.filterwarnings("ignore", "win_type", FutureWarning)
-            kwargs = {attr: getattr(self, attr) for attr in self._attributes}
+        kwargs = {attr: getattr(self, attr) for attr in self._attributes}
 
         # Try to select from a DataFrame, falling back to a Series
         try:

pandas/core/groupby/groupby.py

@@ -1918,7 +1918,12 @@ def rolling(self, *args, **kwargs):
         """
         from pandas.core.window import RollingGroupby
 
-        return RollingGroupby(self, *args, **kwargs)
+        return RollingGroupby(
+            self._selected_obj,
+            *args,
+            _grouper=self.grouper,
+            **kwargs,
+        )
 
     @final
     @Substitution(name="groupby")
@@ -1930,7 +1935,12 @@ def expanding(self, *args, **kwargs):
         """
         from pandas.core.window import ExpandingGroupby
 
-        return ExpandingGroupby(self, *args, **kwargs)
+        return ExpandingGroupby(
+            self._selected_obj,
+            *args,
+            _grouper=self.grouper,
+            **kwargs,
+        )
 
     @final
     @Substitution(name="groupby")
@@ -1941,7 +1951,12 @@ def ewm(self, *args, **kwargs):
         """
         from pandas.core.window import ExponentialMovingWindowGroupby
 
-        return ExponentialMovingWindowGroupby(self, *args, **kwargs)
+        return ExponentialMovingWindowGroupby(
+            self._selected_obj,
+            *args,
+            _grouper=self.grouper,
+            **kwargs,
+        )
 
     @final
     def _fill(self, direction, limit=None):

pandas/core/window/ewm.py

@@ -213,7 +213,15 @@ class ExponentialMovingWindow(BaseWindow):
     4  3.233686
     """
 
-    _attributes = ["com", "min_periods", "adjust", "ignore_na", "axis"]
+    _attributes = [
+        "com",
+        "min_periods",
+        "adjust",
+        "ignore_na",
+        "axis",
+        "halflife",
+        "times",
+    ]
 
     def __init__(
         self,
@@ -227,17 +235,18 @@ def __init__(
         ignore_na: bool = False,
         axis: int = 0,
         times: Optional[Union[str, np.ndarray, FrameOrSeries]] = None,
-        **kwargs,
     ):
-        self.obj = obj
-        self.min_periods = max(int(min_periods), 1)
+        super().__init__(
+            obj=obj,
+            min_periods=max(int(min_periods), 1),
+            on=None,
+            center=False,
+            closed=None,
+            method="single",
+            axis=axis,
+        )
         self.adjust = adjust
         self.ignore_na = ignore_na
-        self.axis = axis
-        self.on = None
-        self.center = False
-        self.closed = None
-        self.method = "single"
         if times is not None:
             if isinstance(times, str):
                 times = self._selected_obj[times]
@@ -556,9 +565,7 @@ class ExponentialMovingWindowGroupby(BaseWindowGroupby, ExponentialMovingWindow)
     Provide an exponential moving window groupby implementation.
     """
 
-    @property
-    def _constructor(self):
-        return ExponentialMovingWindow
+    _attributes = ExponentialMovingWindow._attributes + BaseWindowGroupby._attributes
 
     def _get_window_indexer(self) -> GroupbyIndexer:
         """
@@ -569,7 +576,7 @@ def _get_window_indexer(self) -> GroupbyIndexer:
         GroupbyIndexer
         """
         window_indexer = GroupbyIndexer(
-            groupby_indicies=self._groupby.indices,
+            groupby_indicies=self._grouper.indices,
             window_indexer=ExponentialMovingWindowIndexer,
         )
         return window_indexer

pandas/core/window/expanding.py

@@ -94,9 +94,7 @@ class Expanding(RollingAndExpandingMixin):
 
     _attributes = ["min_periods", "center", "axis", "method"]
 
-    def __init__(
-        self, obj, min_periods=1, center=None, axis=0, method="single", **kwargs
-    ):
+    def __init__(self, obj, min_periods=1, center=None, axis=0, method="single"):
         super().__init__(
             obj=obj, min_periods=min_periods, center=center, axis=axis, method=method
         )
@@ -629,9 +627,7 @@ class ExpandingGroupby(BaseWindowGroupby, Expanding):
     Provide a expanding groupby implementation.
     """
 
-    @property
-    def _constructor(self):
-        return Expanding
+    _attributes = Expanding._attributes + BaseWindowGroupby._attributes
 
     def _get_window_indexer(self) -> GroupbyIndexer:
         """
@@ -642,7 +638,7 @@ def _get_window_indexer(self) -> GroupbyIndexer:
         GroupbyIndexer
         """
         window_indexer = GroupbyIndexer(
-            groupby_indicies=self._groupby.indices,
+            groupby_indicies=self._grouper.indices,
             window_indexer=ExpandingIndexer,
         )
         return window_indexer