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BUG: TimedeltaArray - Index result.name #27962

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Merged
merged 2 commits into from
Aug 19, 2019
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BUG: TimedeltaArray - Index result.name #27962

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9459307
BUG: TimedeltaArray - Index result.name
jbrockmendel Aug 17, 2019
b6440f9
change assert to TypeErrro
jbrockmendel Aug 17, 2019
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5 changes: 4 additions & 1 deletion pandas/core/indexes/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2325,7 +2325,10 @@ def __sub__(self, other):
return Index(np.array(self) - other)

def __rsub__(self, other):
return Index(other - np.array(self))
# wrap Series to ensure we pin name correctly
from pandas import Series

return Index(other - Series(self))

def __and__(self, other):
return self.intersection(other)
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5 changes: 3 additions & 2 deletions pandas/core/ops/array_ops.py
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Expand Up @@ -74,8 +74,9 @@ def masked_arith_op(x, y, op):
result[mask] = op(xrav[mask], yrav[mask])

else:
assert is_scalar(y), type(y)
assert isinstance(x, np.ndarray), type(x)
if not is_scalar(y):
raise TypeError(type(y))

# mask is only meaningful for x
result = np.empty(x.size, dtype=x.dtype)
mask = notna(xrav)
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10 changes: 7 additions & 3 deletions pandas/tests/arithmetic/test_timedelta64.py
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Expand Up @@ -1378,8 +1378,12 @@ def test_td64arr_add_offset_array(self, box):
@pytest.mark.parametrize(
"names", [(None, None, None), ("foo", "bar", None), ("foo", "foo", "foo")]
)
def test_td64arr_sub_offset_index(self, names, box):
def test_td64arr_sub_offset_index(self, names, box_with_array):
# GH#18824, GH#19744
box = box_with_array
xbox = box if box is not tm.to_array else pd.Index
exname = names[2] if box is not tm.to_array else names[1]

if box is pd.DataFrame and names[1] == "bar":
pytest.skip(
"Name propagation for DataFrame does not behave like "
Expand All @@ -1390,11 +1394,11 @@ def test_td64arr_sub_offset_index(self, names, box):
other = pd.Index([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)], name=names[1])

expected = TimedeltaIndex(
[tdi[n] - other[n] for n in range(len(tdi))], freq="infer", name=names[2]
[tdi[n] - other[n] for n in range(len(tdi))], freq="infer", name=exname
)

tdi = tm.box_expected(tdi, box)
expected = tm.box_expected(expected, box)
expected = tm.box_expected(expected, xbox)

# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
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