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FIX: support pandas 0.25 #15007

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Merged
merged 3 commits into from
Aug 9, 2019
Merged

FIX: support pandas 0.25 #15007

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d33d654
FIX: support pandas 0.25
tacaswell Aug 8, 2019
f30de35
STY: fix whitespace
tacaswell Aug 8, 2019
df4b7dc
MNT: use a slightly simpler check odd Index behavior
tacaswell Aug 9, 2019
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8 changes: 7 additions & 1 deletion lib/matplotlib/cbook/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1326,7 +1326,13 @@ def _check_1d(x):
return np.atleast_1d(x)
else:
try:
x[:, None]
ndim = x[:, None].ndim
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you don't want to do a np.asarray here first? That should make it work with older pandas versions, but also robust to potential future changes (eg if pandas starts raising for that)

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we do not want to asarray things we don't have to (in particular because in some cases that can strip units off of things). So long as future versions raises one of the two exceptions caught below it will "just work" and as soon as you decide what exception you are going to raise we can add it.

The point of this is to check if we need to asarray (which in done implicitly in atleast_1d).

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OK, I see. I suppose if we raise an error it will be an IndexError, so that would already be covered then

# 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.
if ndim < 2:
return np.atleast_1d(x)
return x
except (IndexError, TypeError):
return np.atleast_1d(x)
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6 changes: 6 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -5552,6 +5552,12 @@ def test_pandas_errorbar_indexing(pd):
ax.errorbar('x', 'y', xerr='xe', yerr='ye', data=df)


def test_pandas_index_shape(pd):
df = pd.DataFrame({"XX": [4, 5, 6], "YY": [7, 1, 2]})
fig, ax = plt.subplots()
ax.plot(df.index, df['YY'])


def test_pandas_indexing_hist(pd):
ser_1 = pd.Series(data=[1, 2, 2, 3, 3, 4, 4, 4, 4, 5])
ser_2 = ser_1.iloc[1:]
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