change _selected_obj according to self.mutated

Author: MarcoGorelli

pandas/core/frame.py

@@ -7732,7 +7732,6 @@ def count(self, axis=0, level=None, numeric_only=False):
         Lewis     1
         Myla      1
         """
-        breakpoint()
         axis = self._get_axis_number(axis)
         if level is not None:
             return self._count_level(level, axis=axis, numeric_only=numeric_only)

pandas/core/groupby/groupby.py

@@ -6,7 +6,6 @@ class providing the base-class of operations.
 (defined in pandas.core.groupby.generic)
 expose these user-facing objects to provide specific functionality.
 """
-from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
 
 from contextlib import contextmanager
 import datetime
@@ -409,6 +408,7 @@ def __init__(
                 observed=observed,
                 mutated=self.mutated,
             )
+
         self.obj = obj
         self.axis = obj._get_axis_number(axis)
         self.grouper = grouper
@@ -508,8 +508,7 @@ def _get_index(self, name):
     @cache_readonly
     def _selected_obj(self):
         # Note: _selected_obj is always just `self.obj` for SeriesGroupBy
-        breakpoint()
-        if self.as_index:
+        if self.mutated:
             obj = self._obj_with_exclusions
         else:
             obj = self.obj

pandas/core/window/rolling.py

@@ -1173,6 +1173,7 @@ class _Rolling_and_Expanding(_Rolling):
     )
 
     def count(self):
+
         blocks, obj = self._create_blocks()
         results = []
         for b in blocks:
@@ -1186,6 +1187,7 @@ def count(self):
                 closed=self.closed,
             ).sum()
             results.append(result)
+
         return self._wrap_results(results, blocks, obj)
 
     _shared_docs["apply"] = dedent(
@@ -1951,6 +1953,7 @@ def aggregate(self, func, *args, **kwargs):
     @Substitution(name="rolling")
     @Appender(_shared_docs["count"])
     def count(self):
+
         # different impl for freq counting
         if self.is_freq_type:
             window_func = self._get_roll_func("roll_count")

pandas/tests/groupby/test_apply.py

@@ -405,6 +405,7 @@ def f(group):
 
     expected = df.copy()
     expected["v2"] = np.tile([0.0, 0.5, 1], 2)
+
     tm.assert_frame_equal(result, expected)
 
 
@@ -826,7 +827,6 @@ def test_apply_index_has_complex_internals(index):
     # GH 31248
     df = DataFrame({"group": [1, 1, 2], "value": [0, 1, 0]}, index=index)
     result = df.groupby("group").apply(lambda x: x)
-    breakpoint()
     tm.assert_frame_equal(result, df)
 
 

pandas/tests/window/test_rolling.py

@@ -477,13 +477,3 @@ def test_by_column_not_in_values():
     result = r.sum()
     assert "A" not in result.columns
     tm.assert_frame_equal(g.obj, original_obj)  # check for side-effects
-
-    # g = df.groupby("A")
-    # original_obj = g.obj.copy(deep=True)
-    # r = g.rolling(4)
-    # def cust(x):
-    #     breakpoint()
-    #     return getattr(x.rolling(4), 'sum')()
-    # result = r.apply(cust)
-    # assert "A" not in result.columns
-    # tm.assert_frame_equal(g.obj, original_obj)  # check for side-effects