diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index 9f2a75ce3df0..2722b6c8a3be 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -1300,47 +1300,13 @@ def _to_unmasked_float_array(x):
 
 def _check_1d(x):
     """Convert scalars to 1D arrays; pass-through arrays as is."""
+    if hasattr(x, 'to_numpy'):
+        # if we are given an object that creates a numpy, we should use it...
+        x = x.to_numpy()
     if not hasattr(x, 'shape') or len(x.shape) < 1:
         return np.atleast_1d(x)
     else:
-        try:
-            # work around
-            # https://github.com/pandas-dev/pandas/issues/27775 which
-            # means the shape of multi-dimensional slicing is not as
-            # expected.  That this ever worked was an unintentional
-            # quirk of pandas and will raise an exception in the
-            # future.  This slicing warns in pandas >= 1.0rc0 via
-            # https://github.com/pandas-dev/pandas/pull/30588
-            #
-            # < 1.0rc0 : x[:, None].ndim == 1, no warning, custom type
-            # >= 1.0rc1 : x[:, None].ndim == 2, warns, numpy array
-            # future : x[:, None] -> raises
-            #
-            # This code should correctly identify and coerce to a
-            # numpy array all pandas versions.
-            with warnings.catch_warnings(record=True) as w:
-                warnings.filterwarnings(
-                    "always",
-                    category=Warning,
-                    message='Support for multi-dimensional indexing')
-
-                ndim = x[:, None].ndim
-                # we have definitely hit a pandas index or series object
-                # cast to a numpy array.
-                if len(w) > 0:
-                    return np.asanyarray(x)
-            # We have likely hit a pandas object, or at least
-            # something where 2D slicing does not result in a 2D
-            # object.
-            if ndim < 2:
-                return np.atleast_1d(x)
-            return x
-        # In pandas 1.1.0, multidimensional indexing leads to an
-        # AssertionError for some Series objects, but should be
-        # IndexError as described in
-        # https://github.com/pandas-dev/pandas/issues/35527
-        except (AssertionError, IndexError, TypeError):
-            return np.atleast_1d(x)
+        return x
 
 
 def _reshape_2D(X, name):
@@ -1649,7 +1615,7 @@ def index_of(y):
        The x and y values to plot.
     """
     try:
-        return y.index.values, y.values
+        return y.index.to_numpy(), y.to_numpy()
     except AttributeError:
         pass
     try:
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index cc93bfae4976..204e3cbd984f 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -1762,11 +1762,15 @@ def test_bar_hatches(fig_test, fig_ref):
 
 def test_pandas_minimal_plot(pd):
     # smoke test that series and index objcets do not warn
-    x = pd.Series([1, 2], dtype="float64")
-    plt.plot(x, x)
-    plt.plot(x.index, x)
-    plt.plot(x)
-    plt.plot(x.index)
+    for x in [pd.Series([1, 2], dtype="float64"),
+              pd.Series([1, 2], dtype="Float64")]:
+        plt.plot(x, x)
+        plt.plot(x.index, x)
+        plt.plot(x)
+        plt.plot(x.index)
+    df = pd.DataFrame({'col': [1, 2, 3]})
+    plt.plot(df)
+    plt.plot(df, df)
 
 
 @image_comparison(['hist_log'], remove_text=True)