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separate numeric tests so we can isolate division by zero #19336

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merged 9 commits into from
Feb 8, 2018
Merged

separate numeric tests so we can isolate division by zero #19336

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ba9240c
separate numeric tests so we can isolate division by zero
jbrockmendel Jan 22, 2018
c19dff1
fix flipped condition
jbrockmendel Jan 22, 2018
4182089
comment
jbrockmendel Jan 22, 2018
6f734bc
parametrize and dedup tests
jbrockmendel Jan 22, 2018
393a6c8
parametrize with lambdas
jbrockmendel Jan 24, 2018
5e1d39f
requested formatting edits
jbrockmendel Jan 25, 2018
9fb00cc
Merge branch 'master' of https://github.com/pandas-dev/pandas into sp…
jbrockmendel Jan 25, 2018
8fd7e31
Merge branch 'master' of https://github.com/pandas-dev/pandas into sp…
jbrockmendel Feb 1, 2018
4b78542
suggested reformat
jbrockmendel Feb 1, 2018
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192 changes: 98 additions & 94 deletions pandas/tests/series/test_operators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -595,77 +595,81 @@ def test_divide_decimal(self):

assert_series_equal(expected, s)

def test_div(self):
@pytest.mark.parametrize(
'dtype2',
[
np.int64, np.int32, np.int16, np.int8,
np.float64, np.float32, np.float16,
np.uint64, np.uint32,
np.uint16, np.uint8
])
@pytest.mark.parametrize('dtype1', [np.int64, np.float64, np.uint64])
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pls clean the parameterize up here as I suggested

def test_ser_div_ser(self, dtype1, dtype2):
# no longer do integer div for any ops, but deal with the 0's
first = Series([3, 4, 5, 8], name='first').astype(dtype1)
second = Series([0, 0, 0, 3], name='second').astype(dtype2)

with np.errstate(all='ignore'):
# no longer do integer div for any ops, but deal with the 0's
p = DataFrame({'first': [3, 4, 5, 8], 'second': [0, 0, 0, 3]})
result = p['first'] / p['second']
expected = Series(
p['first'].values.astype(float) / p['second'].values,
dtype='float64')
expected.iloc[0:3] = np.inf
assert_series_equal(result, expected)
expected = Series(first.values.astype(np.float64) / second.values,
dtype='float64', name=None)
expected.iloc[0:3] = np.inf

result = p['first'] / 0
expected = Series(np.inf, index=p.index, name='first')
assert_series_equal(result, expected)
result = first / second
assert_series_equal(result, expected)
assert not result.equals(second / first)

p = p.astype('float64')
result = p['first'] / p['second']
expected = Series(p['first'].values / p['second'].values)
assert_series_equal(result, expected)
def test_div_equiv_binop(self):
# Test Series.div as well as Series.__div__
# float/integer issue
# GH#7785
first = pd.Series([1, 0], name='first')
second = pd.Series([-0.01, -0.02], name='second')
expected = Series([-0.01, -np.inf])

p = DataFrame({'first': [3, 4, 5, 8], 'second': [1, 1, 1, 1]})
result = p['first'] / p['second']
assert_series_equal(result, p['first'].astype('float64'),
check_names=False)
assert result.name is None
assert not result.equals(p['second'] / p['first'])

# inf signing
s = Series([np.nan, 1., -1.])
result = s / 0
expected = Series([np.nan, np.inf, -np.inf])
assert_series_equal(result, expected)
result = second.div(first)
assert_series_equal(result, expected, check_names=False)

# float/integer issue
# GH 7785
p = DataFrame({'first': (1, 0), 'second': (-0.01, -0.02)})
expected = Series([-0.01, -np.inf])
result = second / first
assert_series_equal(result, expected)

result = p['second'].div(p['first'])
assert_series_equal(result, expected, check_names=False)
def test_rdiv_zero_compat(self):
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parametrie over 0 with various int/uint dtypes

# GH#8674
zero_array = np.array([0] * 5)
data = np.random.randn(5)
expected = pd.Series([0.] * 5)

result = p['second'] / p['first']
assert_series_equal(result, expected)
result = zero_array / pd.Series(data)
assert_series_equal(result, expected)

# GH 9144
s = Series([-1, 0, 1])
result = pd.Series(zero_array) / data
assert_series_equal(result, expected)

result = 0 / s
expected = Series([0.0, nan, 0.0])
assert_series_equal(result, expected)
result = pd.Series(zero_array) / pd.Series(data)
assert_series_equal(result, expected)

result = s / 0
expected = Series([-inf, nan, inf])
assert_series_equal(result, expected)
def test_div_zero_inf_signs(self):
# GH#9144, inf signing
ser = Series([-1, 0, 1], name='first')
expected = Series([-np.inf, np.nan, np.inf], name='first')

result = s // 0
expected = Series([-inf, nan, inf])
assert_series_equal(result, expected)
result = ser / 0
assert_series_equal(result, expected)

# GH 8674
zero_array = np.array([0] * 5)
data = np.random.randn(5)
expected = pd.Series([0.] * 5)
result = zero_array / pd.Series(data)
assert_series_equal(result, expected)
def test_rdiv_zero(self):
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parametrize

# GH#9144
ser = Series([-1, 0, 1], name='first')
expected = Series([0.0, np.nan, 0.0], name='first')

result = pd.Series(zero_array) / data
assert_series_equal(result, expected)
result = 0 / ser
assert_series_equal(result, expected)

result = pd.Series(zero_array) / pd.Series(data)
assert_series_equal(result, expected)
def test_floordiv_div(self):
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same. see the pattern :>

need to create a zero fixture

# GH#9144
ser = Series([-1, 0, 1], name='first')

result = ser // 0
expected = Series([-inf, nan, inf], name='first')
assert_series_equal(result, expected)


class TestTimedeltaSeriesArithmeticWithIntegers(object):
Expand Down Expand Up @@ -1574,33 +1578,38 @@ def test_dt64_series_add_intlike(self, tz):


class TestSeriesOperators(TestData):
def test_op_method(self):
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can you add a comment to describe what tests this class does

def check(series, other, check_reverse=False):
simple_ops = ['add', 'sub', 'mul', 'floordiv', 'truediv', 'pow']
if not compat.PY3:
simple_ops.append('div')

for opname in simple_ops:
op = getattr(Series, opname)

if op == 'div':
alt = operator.truediv
else:
alt = getattr(operator, opname)

result = op(series, other)
expected = alt(series, other)
assert_almost_equal(result, expected)
if check_reverse:
rop = getattr(Series, "r" + opname)
result = rop(series, other)
expected = alt(other, series)
assert_almost_equal(result, expected)
@pytest.mark.parametrize(
'ts',
[
lambda x: (x, x * 2, False),
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don't write it like this rather split out parameters

@pytest.mark.parametrize(
'ts'
[
    (lamda x: x, lamda x: x[::2], False),
....
])

its slightly longer but much more obvious

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Sometimes I look at the results of these format changes and say "yah, he's right, that is more readable." This isn't one of those times. Doing it anyway.

lambda x: (x, x[::2], False),
lambda x: (x, 5, True),
lambda x: (tm.makeFloatSeries(), tm.makeFloatSeries(), True)
])
@pytest.mark.parametrize('opname', ['add', 'sub', 'mul', 'floordiv',
'truediv', 'div', 'pow'])
def test_op_method(self, opname, ts):
# check that Series.{opname} behaves like Series.__{opname}__,
series, other, check_reverse = ts(self.ts)

if opname == 'div' and compat.PY3:
pytest.skip('div test only for Py3')

op = getattr(Series, opname)

if op == 'div':
alt = operator.truediv
else:
alt = getattr(operator, opname)

check(self.ts, self.ts * 2)
check(self.ts, self.ts[::2])
check(self.ts, 5, check_reverse=True)
check(tm.makeFloatSeries(), tm.makeFloatSeries(), check_reverse=True)
result = op(series, other)
expected = alt(series, other)
assert_almost_equal(result, expected)
if check_reverse:
rop = getattr(Series, "r" + opname)
result = rop(series, other)
expected = alt(other, series)
assert_almost_equal(result, expected)

def test_neg(self):
assert_series_equal(-self.series, -1 * self.series)
Expand Down Expand Up @@ -1992,20 +2001,15 @@ def test_operators_corner(self):
index=self.ts.index[:-5], name='ts')
tm.assert_series_equal(added[:-5], expected)

def test_operators_reverse_object(self):
@pytest.mark.parametrize('op', [operator.add, operator.sub, operator.mul,
operator.truediv, operator.floordiv])
def test_operators_reverse_object(self, op):
# GH 56
arr = Series(np.random.randn(10), index=np.arange(10), dtype=object)

def _check_op(arr, op):
result = op(1., arr)
expected = op(1., arr.astype(float))
assert_series_equal(result.astype(float), expected)

_check_op(arr, operator.add)
_check_op(arr, operator.sub)
_check_op(arr, operator.mul)
_check_op(arr, operator.truediv)
_check_op(arr, operator.floordiv)
result = op(1., arr)
expected = op(1., arr.astype(float))
assert_series_equal(result.astype(float), expected)

def test_arith_ops_df_compat(self):
# GH 1134
Expand Down