From ff8b1a943d61b22ccad2e5ffd59893f0fc4fba69 Mon Sep 17 00:00:00 2001
From: Jody Klymak <jklymak@gmail.com>
Date: Tue, 28 Jan 2020 15:20:18 -0800
Subject: [PATCH] Backport PR #16347: FIX: catch warnings from pandas in
 cbook._check_1d

---
 lib/matplotlib/cbook/__init__.py  | 32 ++++++++++++++++++++++++++-----
 lib/matplotlib/tests/test_axes.py |  9 +++++++++
 2 files changed, 36 insertions(+), 5 deletions(-)

diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index acf6b8fe54ae..d6fcf855f487 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -1326,11 +1326,33 @@ def _check_1d(x):
         return np.atleast_1d(x)
     else:
         try:
-            ndim = x[:, None].ndim
-            # work around https://github.com/pandas-dev/pandas/issues/27775
-            # which mean the shape is not as expected. That this ever worked
-            # was an unintentional quirk of pandas the above line will raise
-            # an exception in the future.
+            # 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=DeprecationWarning,
+                                        module='pandas[.*]')
+
+                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
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 290dfa64664b..4bf3e8724745 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -1669,6 +1669,15 @@ def test_bar_pandas_indexed(pd):
     ax.bar(df.x, 1., width=df.width)
 
 
+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)
+
+
 @image_comparison(['hist_log'], remove_text=True)
 def test_hist_log():
     data0 = np.linspace(0, 1, 200)**3