diff --git a/doc/source/10min.rst b/doc/source/10min.rst
index 53618e008a403..a7557e6e1d1c2 100644
--- a/doc/source/10min.rst
+++ b/doc/source/10min.rst
@@ -51,7 +51,7 @@ Creating a ``DataFrame`` by passing a dict of objects that can be converted to s
                        'F': 'foo'})
    df2
 
-The columns of the resulting ``DataFrame`` have different 
+The columns of the resulting ``DataFrame`` have different
 :ref:`dtypes <basics.dtypes>`.
 
 .. ipython:: python
@@ -65,7 +65,7 @@ will be completed:
 .. ipython::
 
    @verbatim
-   In [1]: df2.<TAB>
+   In [1]: df2.<TAB>  # noqa: E225, E999
    df2.A                  df2.bool
    df2.abs                df2.boxplot
    df2.add                df2.C
@@ -495,7 +495,7 @@ Another example that can be given is:
 Append
 ~~~~~~
 
-Append rows to a dataframe. See the :ref:`Appending <merging.concatenation>` 
+Append rows to a dataframe. See the :ref:`Appending <merging.concatenation>`
 section.
 
 .. ipython:: python
@@ -528,14 +528,14 @@ See the :ref:`Grouping section <groupby>`.
                       'D': np.random.randn(8)})
    df
 
-Grouping and then applying the :meth:`~DataFrame.sum` function to the resulting 
+Grouping and then applying the :meth:`~DataFrame.sum` function to the resulting
 groups.
 
 .. ipython:: python
 
    df.groupby('A').sum()
 
-Grouping by multiple columns forms a hierarchical index, and again we can 
+Grouping by multiple columns forms a hierarchical index, and again we can
 apply the ``sum`` function.
 
 .. ipython:: python
@@ -671,7 +671,7 @@ Convert the raw grades to a categorical data type.
     df["grade"] = df["raw_grade"].astype("category")
     df["grade"]
 
-Rename the categories to more meaningful names (assigning to 
+Rename the categories to more meaningful names (assigning to
 ``Series.cat.categories`` is inplace!).
 
 .. ipython:: python
@@ -720,7 +720,7 @@ See the :ref:`Plotting <visualization>` docs.
    @savefig series_plot_basic.png
    ts.plot()
 
-On a DataFrame, the :meth:`~DataFrame.plot` method is a convenience to plot all 
+On a DataFrame, the :meth:`~DataFrame.plot` method is a convenience to plot all
 of the columns with labels:
 
 .. ipython:: python
diff --git a/setup.cfg b/setup.cfg
index 73a3a6c136b53..3071ac61cfdce 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -76,7 +76,6 @@ exclude =
     doc/source/whatsnew/v0.23.1.rst
     doc/source/whatsnew/v0.23.2.rst
     doc/source/whatsnew/v0.24.0.rst
-    doc/source/10min.rst
     doc/source/basics.rst
     doc/source/contributing_docstring.rst
     doc/source/dsintro.rst