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Backport PR #34721 on branch 1.0.x (Debug CI Issue) #34788

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Merged
merged 1 commit into from
Jun 15, 2020
Merged

Backport PR #34721 on branch 1.0.x (Debug CI Issue) #34788

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2 changes: 2 additions & 0 deletions pandas/compat/numpy/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,8 @@
_np_version_under1p16 = _nlv < LooseVersion("1.16")
_np_version_under1p17 = _nlv < LooseVersion("1.17")
_np_version_under1p18 = _nlv < LooseVersion("1.18")
_np_version_under1p19 = _nlv < LooseVersion("1.19")
_np_version_under1p20 = _nlv < LooseVersion("1.20")
_is_numpy_dev = ".dev" in str(_nlv)


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22 changes: 13 additions & 9 deletions pandas/tests/extension/base/dtype.py
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Expand Up @@ -68,18 +68,22 @@ def test_check_dtype(self, data):
{"A": pd.Series(data, dtype=dtype), "B": data, "C": "foo", "D": 1}
)

# np.dtype('int64') == 'Int64' == 'int64'
# so can't distinguish
if dtype.name == "Int64":
expected = pd.Series([True, True, False, True], index=list("ABCD"))
else:
expected = pd.Series([True, True, False, False], index=list("ABCD"))

# XXX: This should probably be *fixed* not ignored.
# See libops.scalar_compare
# TODO(numpy-1.20): This warnings filter and if block can be removed
# once we require numpy>=1.20
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
result = df.dtypes == str(dtype)
# NumPy>=1.20.0, but not pandas.compat.numpy till there
# is a wheel available with this change.
try:
new_numpy_behavior = np.dtype("int64") != "Int64"
except TypeError:
new_numpy_behavior = True

if dtype.name == "Int64" and not new_numpy_behavior:
expected = pd.Series([True, True, False, True], index=list("ABCD"))
else:
expected = pd.Series([True, True, False, False], index=list("ABCD"))

self.assert_series_equal(result, expected)

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6 changes: 5 additions & 1 deletion pandas/tests/plotting/test_misc.py
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Expand Up @@ -98,13 +98,17 @@ def test_bootstrap_plot(self):
class TestDataFramePlots(TestPlotBase):
@td.skip_if_no_scipy
def test_scatter_matrix_axis(self):
from pandas.plotting._matplotlib.compat import _mpl_ge_3_0_0

scatter_matrix = plotting.scatter_matrix

with tm.RNGContext(42):
df = DataFrame(randn(100, 3))

# we are plotting multiples on a sub-plot
with tm.assert_produces_warning(UserWarning):
with tm.assert_produces_warning(
UserWarning, raise_on_extra_warnings=_mpl_ge_3_0_0()
):
axes = _check_plot_works(
scatter_matrix, filterwarnings="always", frame=df, range_padding=0.1
)
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