diff --git a/doc/source/user_guide/groupby.rst b/doc/source/user_guide/groupby.rst
index 5d8ef7ce02097..3a6ec0bfd6c5c 100644
--- a/doc/source/user_guide/groupby.rst
+++ b/doc/source/user_guide/groupby.rst
@@ -274,15 +274,16 @@ the length of the ``groups`` dict, so it is largely just a convenience:
    df
    gb = df.groupby("gender")
 
-
-.. ipython::
+.. ipython:: python
 
    @verbatim
-   In [1]: gb.<TAB>  # noqa: E225, E999
+   # flake8: noqa
+   In [1]: gb.<TAB>
    gb.agg        gb.boxplot    gb.cummin     gb.describe   gb.filter     gb.get_group  gb.height     gb.last       gb.median     gb.ngroups    gb.plot       gb.rank       gb.std        gb.transform
    gb.aggregate  gb.count      gb.cumprod    gb.dtype      gb.first      gb.groups     gb.hist       gb.max        gb.min        gb.nth        gb.prod       gb.resample   gb.sum        gb.var
    gb.apply      gb.cummax     gb.cumsum     gb.fillna     gb.gender     gb.head       gb.indices    gb.mean       gb.name       gb.ohlc       gb.quantile   gb.size       gb.tail       gb.weight
 
+
 .. _groupby.multiindex:
 
 GroupBy with MultiIndex
@@ -345,6 +346,17 @@ Index level names may be supplied as keys.
 
 More on the ``sum`` function and aggregation later.
 
+When using ``.groupby()`` on a DatFrame with a  MultiIndex, do not specify both ``by`` and ``level``.
+The argument validation should be done in ``.groupby()``, using the name of the specific index.
+
+.. ipython:: python
+
+   df = pd.DataFrame({"col1": ["a", "b", "c"]})
+   df.index = pd.MultiIndex.from_arrays([["a", "a", "b"],
+                                        [1, 2, 1]],
+                                        names=["x", "y"])
+   df.groupby(["col1", "x"])
+
 Grouping DataFrame with Index levels and columns
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 A DataFrame may be grouped by a combination of columns and index levels by