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TST: Check ndarray dtype by default #13088
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Current coverage is 84.14%@@ master #13088 diff @@
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failing here: https://travis-ci.org/pydata/pandas/jobs/127978632 |
np.array(["a", "b", "c"])) | ||
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exp_cat = np.array(["a", "b", "c", "a"], dtype=np.object_) | ||
self.assert_numpy_array_equal(cat.__array__(), exp_cat) |
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can do in a followup, but I suspect some of these tests would be more clear to construct the expected Categorical
and use assert_equal_categorical
(when these were originally written we didn't hav e it).
na, nb = a.size, b.size | ||
if a.shape != b.shape: | ||
from pandas.util.testing import raise_assert_detail | ||
raise_assert_detail(obj, '{0} shapes are different'.format(obj), | ||
a.shape, b.shape) | ||
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if check_dtype and a.dtype != b.dtype: |
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use not com.is_dtype_equal
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thanks @sinhrks |
git diff upstream/master | flake8 --diff
Also did little cleanup of
testing.pyx
andtesting.py
.