matplotlib
diff --git a/‎lib/matplotlib/axes/_axes.py
Lines changed: 2 additions & 2 deletions b/‎lib/matplotlib/axes/_axes.py
Lines changed: 2 additions & 2 deletions
diff --git a/‎lib/matplotlib/cbook/__init__.py
Lines changed: 16 additions & 9 deletions b/‎lib/matplotlib/cbook/__init__.py
Lines changed: 16 additions & 9 deletions
diff --git a/‎lib/matplotlib/dates.py
Lines changed: 2 additions & 3 deletions b/‎lib/matplotlib/dates.py
Lines changed: 2 additions & 3 deletions
diff --git a/‎lib/matplotlib/units.py
Lines changed: 3 additions & 2 deletions b/‎lib/matplotlib/units.py
Lines changed: 3 additions & 2 deletions
         """
 
         def _kde_method(X, coords):
-            if hasattr(X, 'values'):  # support pandas.Series
-                X = X.values
+            # Unpack in case of Pandas object
+            X = cbook._unpack_pandas(X)
             # fallback gracefully if the vector contains only one value
             if np.all(X[0] == X):
                 return (X[0] == coords).astype(float)
 
@@ -1377,15 +1377,8 @@ def _reshape_2D(X, name):
     *name* is used to generate the error message for invalid inputs.
     """
 
-    # unpack if we have a values or to_numpy method.
-    try:
-        X = X.to_numpy()
-    except AttributeError:
-        try:
-            if isinstance(X.values, np.ndarray):
-                X = X.values
-        except AttributeError:
-            pass
+    # Unpack in case of Pandas object
+    X = _unpack_pandas(X)
 
     # Iterate over columns for ndarrays.
     if isinstance(X, np.ndarray):
@@ -2276,3 +2269,17 @@ def _picklable_class_constructor(mixin_class, fmt, attr_name, base_class):
     factory = _make_class_factory(mixin_class, fmt, attr_name)
     cls = factory(base_class)
     return cls.__new__(cls)
+
+
+def _unpack_pandas(x):
+    """Internal helper to extract data from Pandas object."""
+    if hasattr(x, 'to_numpy'):
+        # Assume that any function to_numpy() do actually return a numpy array
+        return x.to_numpy()
+    if hasattr(x, 'values'):
+        xtmp = x.values
+        # For example a dict has a 'values' attribute, but it is not a property
+        # so in this case we do not want to return a function
+        if isinstance(xtmp, np.ndarray):
+            return xtmp
+    return x
@@ -437,9 +437,8 @@ def date2num(d):
     The Gregorian calendar is assumed; this is not universal practice.
     For details see the module docstring.
     """
-    if hasattr(d, "values"):
-        # this unpacks pandas series or dataframes...
-        d = d.values
+    # Unpack in case of Pandas object
+    d = cbook._unpack_pandas(d)
 
     # make an iterable, but save state to unpack later:
     iterable = np.iterable(d)
 
@@ -180,8 +180,9 @@ class Registry(dict):
 
     def get_converter(self, x):
         """Get the converter interface instance for *x*, or None."""
-        if hasattr(x, "values"):
-            x = x.values  # Unpack pandas Series and DataFrames.
+        # Unpack in case of Pandas object
+        x = cbook._unpack_pandas(x)
+
         if isinstance(x, np.ndarray):
             # In case x in a masked array, access the underlying data (only its
             # type matters).  If x is a regular ndarray, getdata() just returns