BUG: DataFrameGroupby std/sem modify grouped column when as_index=False

Author: rhshadrach

doc/source/whatsnew/v1.1.0.rst

@@ -603,6 +603,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.resample` where an ``AmbiguousTimeError`` would be raised when the resulting timezone aware :class:`DatetimeIndex` had a DST transition at midnight (:issue:`25758`)
 - Bug in :meth:`DataFrame.groupby` where a ``ValueError`` would be raised when grouping by a categorical column with read-only categories and ``sort=False`` (:issue:`33410`)
 - Bug in :meth:`GroupBy.first` and :meth:`GroupBy.last` where None is not preserved in object dtype (:issue:`32800`)
+- Bug in :meth:`DataFrameGroupby.std` and :meth:`DataFrameGroupby.sem` would modify grouped-by columns when ``as_index=False`` (:issue:`10355`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/groupby.py

@@ -577,11 +577,11 @@ def _set_group_selection(self):
         ):
             return
 
-        ax = self.obj._info_axis
         groupers = [g.name for g in grp.groupings if g.level is None and g.in_axis]
 
         if len(groupers):
             # GH12839 clear selected obj cache when group selection changes
+            ax = self.obj._info_axis
             self._group_selection = ax.difference(Index(groupers), sort=False).tolist()
             self._reset_cache("_selected_obj")
 
@@ -1275,8 +1275,14 @@ def std(self, ddof: int = 1):
         Series or DataFrame
             Standard deviation of values within each group.
         """
-        # TODO: implement at Cython level?
-        return np.sqrt(self.var(ddof=ddof))
+        result = self.var(ddof=ddof)
+        if self.ndim == 1:
+            result = np.sqrt(result)
+        else:
+            for col in result:
+                if col not in self.exclusions:
+                    result[col] = np.sqrt(result[col])
+        return result
 
     @Substitution(name="groupby")
     @Appender(_common_see_also)
@@ -1301,6 +1307,7 @@ def var(self, ddof: int = 1):
                 "var", alt=lambda x, axis: Series(x).var(ddof=ddof)
             )
         else:
+            # TODO: implement at Cython level?
             func = lambda x: x.var(ddof=ddof)
             with _group_selection_context(self):
                 return self._python_agg_general(func)
@@ -1323,7 +1330,15 @@ def sem(self, ddof: int = 1):
         Series or DataFrame
             Standard error of the mean of values within each group.
         """
-        return self.std(ddof=ddof) / np.sqrt(self.count())
+        result = self.std(ddof=ddof)
+        denom = np.sqrt(self.count())
+        if self.ndim == 1:
+            result /= denom
+        else:
+            for col in result:
+                if col not in self.exclusions:
+                    result[col] /= denom[col]
+        return result
 
     @Substitution(name="groupby")
     @Appender(_common_see_also)

pandas/tests/groupby/test_function.py

@@ -585,6 +585,31 @@ def test_ops_general(op, targop):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.parametrize(
+    "op",
+    [
+        "mean",
+        "median",
+        "std",
+        "var",
+        "sum",
+        "prod",
+        "min",
+        "max",
+        "first",
+        "last",
+        "count",
+        "sem",
+    ],
+)
+def test_ops_not_as_index(op):
+    df = DataFrame(np.random.randint(0, 5, size=(100, 2)), columns=["a", "b"])
+
+    result = getattr(df.groupby("a", as_index=False), op)()
+    expected = getattr(df.groupby("a"), op)().reset_index()
+    tm.assert_frame_equal(result, expected)
+
+
 def test_max_nan_bug():
     raw = """,Date,app,File
 -04-23,2013-04-23 00:00:00,,log080001.log