diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 67779775b8a5..6c1c3285eec5 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -7907,8 +7907,8 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
"""
def _kde_method(X, coords):
- if hasattr(X, 'values'): # support pandas.Series
- X = X.values
+ # Unpack in case of e.g. Pandas or xarray object
+ X = cbook._unpack_to_numpy(X)
# fallback gracefully if the vector contains only one value
if np.all(X[0] == X):
return (X[0] == coords).astype(float)
diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
index 47ff088a1cd4..228df1bf637c 100644
--- a/lib/matplotlib/cbook/__init__.py
+++ b/lib/matplotlib/cbook/__init__.py
@@ -1311,9 +1311,8 @@ 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()
+ # Unpack in case of e.g. Pandas or xarray object
+ x = _unpack_to_numpy(x)
if not hasattr(x, 'shape') or len(x.shape) < 1:
return np.atleast_1d(x)
else:
@@ -1332,15 +1331,8 @@ 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 e.g. Pandas or xarray object
+ X = _unpack_to_numpy(X)
# Iterate over columns for ndarrays.
if isinstance(X, np.ndarray):
@@ -2231,3 +2223,20 @@ 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_to_numpy(x):
+ """Internal helper to extract data from e.g. pandas and xarray objects."""
+ if isinstance(x, np.ndarray):
+ # If numpy, return directly
+ return x
+ 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
diff --git a/lib/matplotlib/dates.py b/lib/matplotlib/dates.py
index c6e327327e08..a6a95ad46b81 100644
--- a/lib/matplotlib/dates.py
+++ b/lib/matplotlib/dates.py
@@ -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 e.g. Pandas or xarray object
+ d = cbook._unpack_to_numpy(d)
# make an iterable, but save state to unpack later:
iterable = np.iterable(d)
diff --git a/lib/matplotlib/testing/conftest.py b/lib/matplotlib/testing/conftest.py
index 996bfbefef80..01e60fea05e4 100644
--- a/lib/matplotlib/testing/conftest.py
+++ b/lib/matplotlib/testing/conftest.py
@@ -125,3 +125,10 @@ def pd():
except ImportError:
pass
return pd
+
+
+@pytest.fixture
+def xr():
+ """Fixture to import xarray."""
+ xr = pytest.importorskip('xarray')
+ return xr
diff --git a/lib/matplotlib/tests/conftest.py b/lib/matplotlib/tests/conftest.py
index f051470f777c..06c6d150f31b 100644
--- a/lib/matplotlib/tests/conftest.py
+++ b/lib/matplotlib/tests/conftest.py
@@ -1,3 +1,3 @@
from matplotlib.testing.conftest import (mpl_test_settings,
pytest_configure, pytest_unconfigure,
- pd)
+ pd, xr)
diff --git a/lib/matplotlib/tests/test_cbook.py b/lib/matplotlib/tests/test_cbook.py
index dcb855f73ce7..65956ba9ceea 100644
--- a/lib/matplotlib/tests/test_cbook.py
+++ b/lib/matplotlib/tests/test_cbook.py
@@ -680,14 +680,37 @@ def test_reshape2d_pandas(pd):
for x, xnew in zip(X.T, Xnew):
np.testing.assert_array_equal(x, xnew)
+
+def test_reshape2d_xarray(xr):
+ # separate to allow the rest of the tests to run if no xarray...
X = np.arange(30).reshape(10, 3)
- x = pd.DataFrame(X, columns=["a", "b", "c"])
+ x = xr.DataArray(X, dims=["x", "y"])
Xnew = cbook._reshape_2D(x, 'x')
# Need to check each row because _reshape_2D returns a list of arrays:
for x, xnew in zip(X.T, Xnew):
np.testing.assert_array_equal(x, xnew)
+def test_index_of_pandas(pd):
+ # separate to allow the rest of the tests to run if no pandas...
+ X = np.arange(30).reshape(10, 3)
+ x = pd.DataFrame(X, columns=["a", "b", "c"])
+ Idx, Xnew = cbook.index_of(x)
+ np.testing.assert_array_equal(X, Xnew)
+ IdxRef = np.arange(10)
+ np.testing.assert_array_equal(Idx, IdxRef)
+
+
+def test_index_of_xarray(xr):
+ # separate to allow the rest of the tests to run if no xarray...
+ X = np.arange(30).reshape(10, 3)
+ x = xr.DataArray(X, dims=["x", "y"])
+ Idx, Xnew = cbook.index_of(x)
+ np.testing.assert_array_equal(X, Xnew)
+ IdxRef = np.arange(10)
+ np.testing.assert_array_equal(Idx, IdxRef)
+
+
def test_contiguous_regions():
a, b, c = 3, 4, 5
# Starts and ends with True
diff --git a/lib/matplotlib/units.py b/lib/matplotlib/units.py
index f0a0072abf67..910509f20310 100644
--- a/lib/matplotlib/units.py
+++ b/lib/matplotlib/units.py
@@ -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 e.g. Pandas or xarray object
+ x = cbook._unpack_to_numpy(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
diff --git a/requirements/testing/extra.txt b/requirements/testing/extra.txt
index e5bb5d86a667..248e86b53e27 100644
--- a/requirements/testing/extra.txt
+++ b/requirements/testing/extra.txt
@@ -7,3 +7,4 @@ pandas!=0.25.0
pikepdf
pytz
pywin32; sys.platform == 'win32'
+xarray
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