diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
index 737f423af91c..189daacf05c2 100644
--- a/lib/matplotlib/axes/_base.py
+++ b/lib/matplotlib/axes/_base.py
@@ -15,7 +15,7 @@
 from matplotlib import _api, cbook, docstring, offsetbox
 import matplotlib.artist as martist
 import matplotlib.axis as maxis
-from matplotlib.cbook import _OrderedSet, _check_1d, index_of
+from matplotlib.cbook import _OrderedSet, index_of
 import matplotlib.collections as mcoll
 import matplotlib.colors as mcolors
 import matplotlib.font_manager as font_manager
@@ -484,8 +484,8 @@ def _plot_args(self, tup, kwargs, return_kwargs=False):
                 kw[prop_name] = val
 
         if len(xy) == 2:
-            x = _check_1d(xy[0])
-            y = _check_1d(xy[1])
+            x = np.atleast_1d(xy[0])
+            y = np.atleast_1d(xy[1])
         else:
             x, y = index_of(xy[-1])
 
diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index efaabd1e09d4..01716ce3de55 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -1300,47 +1300,7 @@ def _to_unmasked_float_array(x):
 
 def _check_1d(x):
     """Convert scalars to 1D arrays; pass-through arrays as is."""
-    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 np.atleast_1d(x)
 
 
 def _reshape_2D(X, name):
@@ -1653,7 +1613,7 @@ def index_of(y):
     except AttributeError:
         pass
     try:
-        y = _check_1d(y)
+        y = np.atleast_1d(y)
     except (np.VisibleDeprecationWarning, ValueError):
         # NumPy 1.19 will warn on ragged input, and we can't actually use it.
         pass