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Fixed IntegerArray division by 0 #30183

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Merged
merged 3 commits into from
Dec 11, 2019
Merged

Fixed IntegerArray division by 0 #30183

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81b18ca
Fixed IntegerArray division by 0
TomAugspurger Dec 10, 2019
5374d8b
fixed merge conflict
TomAugspurger Dec 10, 2019
f0264f9
negative
TomAugspurger Dec 10, 2019
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.0.0.rst
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Expand Up @@ -856,6 +856,7 @@ Other
- Bug in :meth:`DataFrame.append` that raised ``IndexError`` when appending with empty list (:issue:`28769`)
- Fix :class:`AbstractHolidayCalendar` to return correct results for
years after 2030 (now goes up to 2200) (:issue:`27790`)
- Fixed :class:`IntegerArray` returning ``NA`` rather than ``inf`` for operations dividing by 0 (:issue:`27398`)
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This is a bit confusingly worded I think, as I would interpret this that it now returns NaN and no longer inf, while it is the other way around?

Also NA -> NaN, as the result is about floats with NaNs

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for non-trivially to understand changes we usually have a sub-section, but up to you.

- Bug in :meth:`Series.count` raises if use_inf_as_na is enabled (:issue:`29478`)


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7 changes: 1 addition & 6 deletions pandas/core/arrays/integer.py
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Expand Up @@ -700,11 +700,6 @@ def _maybe_mask_result(self, result, mask, other, op_name):
op_name : str
"""

# may need to fill infs
# and mask wraparound
if is_float_dtype(result):
mask |= (result == np.inf) | (result == -np.inf)
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i think this line was at the root of #27829, so this might fix that

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I think you're correct.


# if we have a float operand we are by-definition
# a float result
# or our op is a divide
Expand Down Expand Up @@ -748,7 +743,7 @@ def integer_arithmetic_method(self, other):

# nans propagate
if mask is None:
mask = self._mask
mask = self._mask.copy()
else:
mask = self._mask | mask

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11 changes: 11 additions & 0 deletions pandas/tests/arrays/test_integer.py
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Expand Up @@ -339,6 +339,13 @@ def test_error(self, data, all_arithmetic_operators):
with pytest.raises(NotImplementedError):
opa(np.arange(len(s)).reshape(-1, len(s)))

def test_divide_by_zero(self):
# https://github.com/pandas-dev/pandas/issues/27398
a = pd.array([0, 1, -1, None], dtype="Int64")
result = a / 0
expected = np.array([np.nan, np.inf, -np.inf, np.nan])
tm.assert_numpy_array_equal(result, expected)

def test_pow(self):
# https://github.com/pandas-dev/pandas/issues/22022
a = integer_array([1, np.nan, np.nan, 1])
Expand Down Expand Up @@ -389,6 +396,10 @@ def test_compare_array(self, data, all_compare_operators):
other = pd.Series([0] * len(data))
self._compare_other(data, op_name, other)

def test_no_shared_mask(self, data):
result = data + 1
assert np.shares_memory(result._mask, data._mask) is False
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i didnt know about shares_memory, neat!



class TestCasting:
@pytest.mark.parametrize("dropna", [True, False])
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