Skip to content

Backport PR #16347: FIX: catch warnings from pandas in cbook._check_1d #16362

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jan 29, 2020
Merged

Backport PR #16347: FIX: catch warnings from pandas in cbook._check_1d #16362

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 27 additions & 5 deletions lib/matplotlib/cbook/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1399,11 +1399,33 @@ 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
Expand Down
9 changes: 9 additions & 0 deletions lib/matplotlib/tests/test_axes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1600,6 +1600,15 @@ 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(baseline_images=['hist_log'],
remove_text=True)
def test_hist_log():
Expand Down