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

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Merged
merged 3 commits into from
Jan 28, 2020
Merged

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

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c7eddd6
FIX: catch warnings from pandas in cbook._check_1d
tacaswell Jan 27, 2020
676f3eb
DOC: clarified comments in code about what this code is doing
tacaswell Jan 28, 2020
77e7b31
TST: renamed test to be less idiomatic
tacaswell Jan 28, 2020
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32 changes: 27 additions & 5 deletions lib/matplotlib/cbook/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1367,11 +1367,33 @@ 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[.*]')
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does this mean we're just kicking the can down the road and will need yet another fix when pandas actually change this behavior?

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The change will be to raise one of the Exceptions we already catch below so we will still be happy.

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fair enough


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
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9 changes: 9 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -1695,6 +1695,15 @@ 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
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