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Followup Cleanup DTI test_arithmetic, ASV #19149

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Merged
merged 12 commits into from
Jan 10, 2018
Merged

Followup Cleanup DTI test_arithmetic, ASV #19149

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8b84d7b
remove asv for Timestamp.offset since it no longer exists
jbrockmendel Jan 9, 2018
a04fe29
parametrize test, extend Series test to DatetimeIndex, fix un-run cases
jbrockmendel Jan 9, 2018
c4b0a19
reindent
jbrockmendel Jan 9, 2018
72bc0a3
parametrize normalize, comment, prettify
jbrockmendel Jan 9, 2018
4dab645
Merge branch 'master' of https://github.com/pandas-dev/pandas into fo…
jbrockmendel Jan 10, 2018
1c0bb72
dont zip
jbrockmendel Jan 10, 2018
39bd287
remove unnecesary
jbrockmendel Jan 10, 2018
262c231
cleanup
jbrockmendel Jan 10, 2018
1bbfa4f
un-xfail Timedelta __rdiv__ test
jbrockmendel Jan 10, 2018
26f805a
break up and parametrize big tests
jbrockmendel Jan 10, 2018
0127f2a
add missing assert_series_equal
jbrockmendel Jan 10, 2018
40a7c6a
Separate and parametrize mul/div dt64 test
jbrockmendel Jan 10, 2018
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3 changes: 0 additions & 3 deletions asv_bench/benchmarks/timestamp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,9 +36,6 @@ def setup(self, tz, freq):
def time_tz(self, tz, freq):
self.ts.tz

def time_offset(self, tz, freq):
self.ts.offset

def time_dayofweek(self, tz, freq):
self.ts.dayofweek

Expand Down
185 changes: 104 additions & 81 deletions pandas/tests/indexes/datetimes/test_arithmetic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -447,6 +447,110 @@ def test_dti_with_offset_series(self, tz, names):
tm.assert_series_equal(res3, expected_sub)


@pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],
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don't use zip

[tm.assert_series_equal,
tm.assert_index_equal]))
def test_dt64_with_offset_array(klass, assert_func):
# GH#10699
# array of offsets
box = Series if klass is Series else pd.Index
with tm.assert_produces_warning(PerformanceWarning):
s = klass([Timestamp('2000-1-1'), Timestamp('2000-2-1')])
result = s + box([pd.offsets.DateOffset(years=1),
pd.offsets.MonthEnd()])
exp = klass([Timestamp('2001-1-1'), Timestamp('2000-2-29')])
assert_func(result, exp)

# same offset
result = s + box([pd.offsets.DateOffset(years=1),
pd.offsets.DateOffset(years=1)])
exp = klass([Timestamp('2001-1-1'), Timestamp('2001-2-1')])
assert_func(result, exp)


@pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],
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i don't like the zip here, rather use a list of tuples

[tm.assert_series_equal,
tm.assert_index_equal]))
def test_dt64_with_DateOffsets_relativedelta(klass, assert_func):
# GH#10699
vec = klass([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-03-31'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31'),
Timestamp('2000-05-15'),
Timestamp('2001-06-15')])

# DateOffset relativedelta fastpath
relative_kwargs = [('years', 2), ('months', 5), ('days', 3),
('hours', 5), ('minutes', 10), ('seconds', 2),
('microseconds', 5)]
for i, kwd in enumerate(relative_kwargs):
op = pd.DateOffset(**dict([kwd]))
assert_func(klass([x + op for x in vec]), vec + op)
assert_func(klass([x - op for x in vec]), vec - op)
op = pd.DateOffset(**dict(relative_kwargs[:i + 1]))
assert_func(klass([x + op for x in vec]), vec + op)
assert_func(klass([x - op for x in vec]), vec - op)


@pytest.mark.parametrize('cls_name', [
'YearBegin', ('YearBegin', {'month': 5}),
'YearEnd', ('YearEnd', {'month': 5}),
'MonthBegin', 'MonthEnd',
'SemiMonthEnd', 'SemiMonthBegin',
'Week', ('Week', {'weekday': 3}),
'BusinessDay', 'BDay', 'QuarterEnd', 'QuarterBegin',
'CustomBusinessDay', 'CDay', 'CBMonthEnd',
'CBMonthBegin', 'BMonthBegin', 'BMonthEnd',
'BusinessHour', 'BYearBegin', 'BYearEnd',
'BQuarterBegin', ('LastWeekOfMonth', {'weekday': 2}),
('FY5253Quarter', {'qtr_with_extra_week': 1,
'startingMonth': 1,
'weekday': 2,
'variation': 'nearest'}),
('FY5253', {'weekday': 0, 'startingMonth': 2, 'variation': 'nearest'}),
('WeekOfMonth', {'weekday': 2, 'week': 2}),
'Easter', ('DateOffset', {'day': 4}),
('DateOffset', {'month': 5})])
@pytest.mark.parametrize('normalize', [True, False])
@pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],
[tm.assert_series_equal,
tm.assert_index_equal]))
def test_dt64_with_DateOffsets(klass, assert_func, normalize, cls_name):
# GH#10699
# assert these are equal on a piecewise basis
vec = klass([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-03-31'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31'),
Timestamp('2000-05-15'),
Timestamp('2001-06-15')])

if isinstance(cls_name, tuple):
# If cls_name param is a tuple, then 2nd entry is kwargs for
# the offset constructor
cls_name, kwargs = cls_name
else:
cls_name = cls_name
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remove cls_name = cls_name

kwargs = {}

with warnings.catch_warnings(record=True):
for n in [0, 5]:
if (cls_name in ['WeekOfMonth', 'LastWeekOfMonth',
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comment on why you are skipping the other cases

'FY5253Quarter', 'FY5253'] and n == 0):
continue
offset = getattr(pd.offsets, cls_name)(n,
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format like

offset = getattr(pd.offsets, cls_name)
    n, normalize=normalize, **kwargs)

normalize=normalize,
**kwargs)
assert_func(klass([x + offset for x in vec]), vec + offset)
assert_func(klass([x - offset for x in vec]), vec - offset)
assert_func(klass([offset + x for x in vec]), offset + vec)


# GH 10699
@pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],
[tm.assert_series_equal,
Expand Down Expand Up @@ -480,84 +584,3 @@ def test_datetime64_with_DateOffset(klass, assert_func):
Timestamp('2000-02-29', tz='US/Central')], name='a')
assert_func(result, exp)
assert_func(result2, exp)

# array of offsets - valid for Series only
if klass is Series:
with tm.assert_produces_warning(PerformanceWarning):
s = klass([Timestamp('2000-1-1'), Timestamp('2000-2-1')])
result = s + Series([pd.offsets.DateOffset(years=1),
pd.offsets.MonthEnd()])
exp = klass([Timestamp('2001-1-1'), Timestamp('2000-2-29')
])
assert_func(result, exp)

# same offset
result = s + Series([pd.offsets.DateOffset(years=1),
pd.offsets.DateOffset(years=1)])
exp = klass([Timestamp('2001-1-1'), Timestamp('2001-2-1')])
assert_func(result, exp)

s = klass([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-03-31'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31'),
Timestamp('2000-05-15'),
Timestamp('2001-06-15')])

# DateOffset relativedelta fastpath
relative_kwargs = [('years', 2), ('months', 5), ('days', 3),
('hours', 5), ('minutes', 10), ('seconds', 2),
('microseconds', 5)]
for i, kwd in enumerate(relative_kwargs):
op = pd.DateOffset(**dict([kwd]))
assert_func(klass([x + op for x in s]), s + op)
assert_func(klass([x - op for x in s]), s - op)
op = pd.DateOffset(**dict(relative_kwargs[:i + 1]))
assert_func(klass([x + op for x in s]), s + op)
assert_func(klass([x - op for x in s]), s - op)

# assert these are equal on a piecewise basis
offsets = ['YearBegin', ('YearBegin', {'month': 5}),
'YearEnd', ('YearEnd', {'month': 5}),
'MonthBegin', 'MonthEnd',
'SemiMonthEnd', 'SemiMonthBegin',
'Week', ('Week', {'weekday': 3}),
'BusinessDay', 'BDay', 'QuarterEnd', 'QuarterBegin',
'CustomBusinessDay', 'CDay', 'CBMonthEnd',
'CBMonthBegin', 'BMonthBegin', 'BMonthEnd',
'BusinessHour', 'BYearBegin', 'BYearEnd',
'BQuarterBegin', ('LastWeekOfMonth', {'weekday': 2}),
('FY5253Quarter', {'qtr_with_extra_week': 1,
'startingMonth': 1,
'weekday': 2,
'variation': 'nearest'}),
('FY5253', {'weekday': 0,
'startingMonth': 2,
'variation':
'nearest'}),
('WeekOfMonth', {'weekday': 2,
'week': 2}),
'Easter', ('DateOffset', {'day': 4}),
('DateOffset', {'month': 5})]

with warnings.catch_warnings(record=True):
for normalize in (True, False):
for do in offsets:
if isinstance(do, tuple):
do, kwargs = do
else:
do = do
kwargs = {}

for n in [0, 5]:
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@jbrockmendel jbrockmendel Jan 9, 2018 •
edited
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I'm pretty sure that this for n in [0, 5]: down through line 563557 is intended to have one fewer level of indentation. That change is implemented up in test_dt64_with_DateOffsets.

if (do in ['WeekOfMonth', 'LastWeekOfMonth',
'FY5253Quarter', 'FY5253'] and n == 0):
continue
op = getattr(pd.offsets, do)(n,
normalize=normalize,
**kwargs)
assert_func(klass([x + op for x in s]), s + op)
assert_func(klass([x - op for x in s]), s - op)
assert_func(klass([op + x for x in s]), op + s)