reverting some changes

Author: ApoorvApoorv

pandas/core/series.py

@@ -1816,7 +1816,6 @@ def _set_name(
         Parrot     20.0
         Name: Max Speed, dtype: float64
 
-        We can pass a of values to group the `Series` data by custom labels:
 
         >>> ser.groupby(["a", "b", "a", "b"]).mean()
         a    210.0
@@ -1837,8 +1836,6 @@ def _set_name(
         Parrot     25.0
         Name: Max Speed, dtype: float64
 
-        We can group by a condition applied to the `Series` values:
-
         >>> ser.groupby(ser > 100).mean()
         Max Speed
         False     25.0
@@ -1868,9 +1865,6 @@ def _set_name(
         Parrot     25.0
         Name: Max Speed, dtype: float64
 
-        We can also group by the `Type` level of the hierarchical index
-        to get the mean speed for each type:
-
         >>> ser.groupby(level="Type").mean()
         Type
         Captive    210.0
@@ -1886,17 +1880,12 @@ def _set_name(
         b    3
         dtype: int64
 
-        To include `NA` values in the group keys, set `dropna=False`:
-
         >>> ser.groupby(level=0, dropna=False).sum()
         a    3
         b    3
         NaN  3
         dtype: int64
 
-        We can also group by a custom with `NaN` values to handle
-        missing group labels:
-
         >>> arrays = ['Falcon', 'Falcon', 'Parrot', 'Parrot']
         >>> ser = pd.Series([390., 350., 30., 20.], index=arrays, name="Max Speed")
         >>> ser.groupby(["a", "b", "a", np.nan]).mean()