Python pandas.offsets() Examples
The following are 30
code examples of pandas.offsets().
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Example #1
| Source File: test_datetime64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_dti_add_offset_index(self, tz_naive_fixture, names):
# GH#18849, GH#19744
tz = tz_naive_fixture
dti = pd.date_range('2017-01-01', periods=2, tz=tz, name=names[0])
other = pd.Index([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
name=names[1])
with tm.assert_produces_warning(PerformanceWarning,
clear=[pd.core.arrays.datetimelike]):
res = dti + other
expected = DatetimeIndex([dti[n] + other[n] for n in range(len(dti))],
name=names[2], freq='infer')
tm.assert_index_equal(res, expected)
with tm.assert_produces_warning(PerformanceWarning,
clear=[pd.core.arrays.datetimelike]):
res2 = other + dti
tm.assert_index_equal(res2, expected)
Example #2
| Source File: test_timedelta64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_td64arr_sub_offset_index(self, names, box):
# GH#18824, GH#19744
if box is pd.DataFrame and names[1] == 'bar':
pytest.skip("Name propagation for DataFrame does not behave like "
"it does for Index/Series")
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'],
name=names[0])
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 = tm.box_expected(tdi, box)
expected = tm.box_expected(expected, box)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = PerformanceWarning if box is not pd.DataFrame else None
with tm.assert_produces_warning(warn):
res = tdi - other
tm.assert_equal(res, expected)
Example #3
| Source File: test_datetime64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_dt64arr_series_sub_tick_DateOffset(self, box_with_array):
# GH#4532
# operate with pd.offsets
ser = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
expected = Series([Timestamp('20130101 9:00:55'),
Timestamp('20130101 9:01:55')])
ser = tm.box_expected(ser, box_with_array)
expected = tm.box_expected(expected, box_with_array)
result = ser - pd.offsets.Second(5)
tm.assert_equal(result, expected)
result2 = -pd.offsets.Second(5) + ser
tm.assert_equal(result2, expected)
with pytest.raises(TypeError):
pd.offsets.Second(5) - ser
Example #4
| Source File: test_timedelta64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_td64arr_add_offset_array(self, box):
# GH#18849
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
expected = TimedeltaIndex([tdi[n] + other[n] for n in range(len(tdi))],
freq='infer')
tdi = tm.box_expected(tdi, box)
expected = tm.box_expected(expected, box)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = PerformanceWarning if box is not pd.DataFrame else None
with tm.assert_produces_warning(warn):
res = tdi + other
tm.assert_equal(res, expected)
with tm.assert_produces_warning(warn):
res2 = other + tdi
tm.assert_equal(res2, expected)
Example #5
| Source File: test_timedelta64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_td64arr_addsub_anchored_offset_arraylike(self, obox,
box_with_array):
# GH#18824
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
tdi = tm.box_expected(tdi, box_with_array)
anchored = obox([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
# addition/subtraction ops with anchored offsets should issue
# a PerformanceWarning and _then_ raise a TypeError.
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
tdi + anchored
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
anchored + tdi
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
tdi - anchored
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
anchored - tdi
Example #6
| Source File: test_timedelta64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_td64arr_sub_offset_array(self, box_with_array):
# GH#18824
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
expected = TimedeltaIndex([tdi[n] - other[n] for n in range(len(tdi))],
freq='infer')
tdi = tm.box_expected(tdi, box_with_array)
expected = tm.box_expected(expected, box_with_array)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = None if box_with_array is pd.DataFrame else PerformanceWarning
with tm.assert_produces_warning(warn):
res = tdi - other
tm.assert_equal(res, expected)
Example #7
| Source File: test_arithmetic.py From twitter-stock-recommendation with MIT License | 6 votes |
|
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)
Example #8
| Source File: test_operators.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_dt64_series_add_mixed_tick_DateOffset(self):
# GH 4532
# operate with pd.offsets
s = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
result = s + pd.offsets.Milli(5)
result2 = pd.offsets.Milli(5) + s
expected = Series([Timestamp('20130101 9:01:00.005'),
Timestamp('20130101 9:02:00.005')])
assert_series_equal(result, expected)
assert_series_equal(result2, expected)
result = s + pd.offsets.Minute(5) + pd.offsets.Milli(5)
expected = Series([Timestamp('20130101 9:06:00.005'),
Timestamp('20130101 9:07:00.005')])
assert_series_equal(result, expected)
Example #9
| Source File: test_arithmetic.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_dti_with_offset_series(self, tz, names):
# GH#18849
dti = pd.date_range('2017-01-01', periods=2, tz=tz, name=names[0])
other = Series([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
name=names[1])
expected_add = Series([dti[n] + other[n] for n in range(len(dti))],
name=names[2])
with tm.assert_produces_warning(PerformanceWarning):
res = dti + other
tm.assert_series_equal(res, expected_add)
with tm.assert_produces_warning(PerformanceWarning):
res2 = other + dti
tm.assert_series_equal(res2, expected_add)
expected_sub = Series([dti[n] - other[n] for n in range(len(dti))],
name=names[2])
with tm.assert_produces_warning(PerformanceWarning):
res3 = dti - other
tm.assert_series_equal(res3, expected_sub)
Example #10
| Source File: test_datetime64.py From recruit with Apache License 2.0 | 6 votes |
|
def test_dt64_series_add_mixed_tick_DateOffset(self):
# GH#4532
# operate with pd.offsets
s = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
result = s + pd.offsets.Milli(5)
result2 = pd.offsets.Milli(5) + s
expected = Series([Timestamp('20130101 9:01:00.005'),
Timestamp('20130101 9:02:00.005')])
tm.assert_series_equal(result, expected)
tm.assert_series_equal(result2, expected)
result = s + pd.offsets.Minute(5) + pd.offsets.Milli(5)
expected = Series([Timestamp('20130101 9:06:00.005'),
Timestamp('20130101 9:07:00.005')])
tm.assert_series_equal(result, expected)
Example #11
| Source File: test_arithmetic.py From vnpy_crypto with MIT License | 6 votes |
|
def test_dti_with_offset_series(self, tz, names):
# GH#18849
dti = pd.date_range('2017-01-01', periods=2, tz=tz, name=names[0])
other = Series([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
name=names[1])
expected_add = Series([dti[n] + other[n] for n in range(len(dti))],
name=names[2])
with tm.assert_produces_warning(PerformanceWarning):
res = dti + other
tm.assert_series_equal(res, expected_add)
with tm.assert_produces_warning(PerformanceWarning):
res2 = other + dti
tm.assert_series_equal(res2, expected_add)
expected_sub = Series([dti[n] - other[n] for n in range(len(dti))],
name=names[2])
with tm.assert_produces_warning(PerformanceWarning):
res3 = dti - other
tm.assert_series_equal(res3, expected_sub)
Example #12
| Source File: test_arithmetic.py From vnpy_crypto with MIT License | 6 votes |
|
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)
Example #13
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_dti_add_offset_index(self, tz_naive_fixture, names):
# GH#18849, GH#19744
tz = tz_naive_fixture
dti = pd.date_range('2017-01-01', periods=2, tz=tz, name=names[0])
other = pd.Index([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
name=names[1])
with tm.assert_produces_warning(PerformanceWarning,
clear=[pd.core.arrays.datetimelike]):
res = dti + other
expected = DatetimeIndex([dti[n] + other[n] for n in range(len(dti))],
name=names[2], freq='infer')
tm.assert_index_equal(res, expected)
with tm.assert_produces_warning(PerformanceWarning,
clear=[pd.core.arrays.datetimelike]):
res2 = other + dti
tm.assert_index_equal(res2, expected)
Example #14
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_dt64_series_add_mixed_tick_DateOffset(self):
# GH#4532
# operate with pd.offsets
s = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
result = s + pd.offsets.Milli(5)
result2 = pd.offsets.Milli(5) + s
expected = Series([Timestamp('20130101 9:01:00.005'),
Timestamp('20130101 9:02:00.005')])
tm.assert_series_equal(result, expected)
tm.assert_series_equal(result2, expected)
result = s + pd.offsets.Minute(5) + pd.offsets.Milli(5)
expected = Series([Timestamp('20130101 9:06:00.005'),
Timestamp('20130101 9:07:00.005')])
tm.assert_series_equal(result, expected)
Example #15
| Source File: test_operators.py From vnpy_crypto with MIT License | 6 votes |
|
def test_dt64_series_add_mixed_tick_DateOffset(self):
# GH 4532
# operate with pd.offsets
s = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
result = s + pd.offsets.Milli(5)
result2 = pd.offsets.Milli(5) + s
expected = Series([Timestamp('20130101 9:01:00.005'),
Timestamp('20130101 9:02:00.005')])
assert_series_equal(result, expected)
assert_series_equal(result2, expected)
result = s + pd.offsets.Minute(5) + pd.offsets.Milli(5)
expected = Series([Timestamp('20130101 9:06:00.005'),
Timestamp('20130101 9:07:00.005')])
assert_series_equal(result, expected)
Example #16
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_dt64arr_series_sub_tick_DateOffset(self, box_with_array):
# GH#4532
# operate with pd.offsets
ser = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
expected = Series([Timestamp('20130101 9:00:55'),
Timestamp('20130101 9:01:55')])
ser = tm.box_expected(ser, box_with_array)
expected = tm.box_expected(expected, box_with_array)
result = ser - pd.offsets.Second(5)
tm.assert_equal(result, expected)
result2 = -pd.offsets.Second(5) + ser
tm.assert_equal(result2, expected)
with pytest.raises(TypeError):
pd.offsets.Second(5) - ser
Example #17
| Source File: test_timedelta64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_td64arr_addsub_anchored_offset_arraylike(self, obox,
box_with_array):
# GH#18824
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
tdi = tm.box_expected(tdi, box_with_array)
anchored = obox([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
# addition/subtraction ops with anchored offsets should issue
# a PerformanceWarning and _then_ raise a TypeError.
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
tdi + anchored
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
anchored + tdi
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
tdi - anchored
with pytest.raises(TypeError):
with tm.assert_produces_warning(PerformanceWarning):
anchored - tdi
Example #18
| Source File: test_timedelta64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_td64arr_add_offset_array(self, box):
# GH#18849
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
expected = TimedeltaIndex([tdi[n] + other[n] for n in range(len(tdi))],
freq='infer')
tdi = tm.box_expected(tdi, box)
expected = tm.box_expected(expected, box)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = PerformanceWarning if box is not pd.DataFrame else None
with tm.assert_produces_warning(warn):
res = tdi + other
tm.assert_equal(res, expected)
with tm.assert_produces_warning(warn):
res2 = other + tdi
tm.assert_equal(res2, expected)
Example #19
| Source File: test_timedelta64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_td64arr_sub_offset_index(self, names, box):
# GH#18824, GH#19744
if box is pd.DataFrame and names[1] == 'bar':
pytest.skip("Name propagation for DataFrame does not behave like "
"it does for Index/Series")
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'],
name=names[0])
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 = tm.box_expected(tdi, box)
expected = tm.box_expected(expected, box)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = PerformanceWarning if box is not pd.DataFrame else None
with tm.assert_produces_warning(warn):
res = tdi - other
tm.assert_equal(res, expected)
Example #20
| Source File: test_timedelta64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_td64arr_sub_offset_array(self, box_with_array):
# GH#18824
tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
expected = TimedeltaIndex([tdi[n] - other[n] for n in range(len(tdi))],
freq='infer')
tdi = tm.box_expected(tdi, box_with_array)
expected = tm.box_expected(expected, box_with_array)
# The DataFrame operation is transposed and so operates as separate
# scalar operations, which do not issue a PerformanceWarning
warn = None if box_with_array is pd.DataFrame else PerformanceWarning
with tm.assert_produces_warning(warn):
res = tdi - other
tm.assert_equal(res, expected)
Example #21
| Source File: test_arithmetic.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_datetime64_with_DateOffset(klass, assert_func):
s = klass(date_range('2000-01-01', '2000-01-31'), name='a')
result = s + pd.DateOffset(years=1)
result2 = pd.DateOffset(years=1) + s
exp = klass(date_range('2001-01-01', '2001-01-31'), name='a')
assert_func(result, exp)
assert_func(result2, exp)
result = s - pd.DateOffset(years=1)
exp = klass(date_range('1999-01-01', '1999-01-31'), name='a')
assert_func(result, exp)
s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
result = s + pd.offsets.Day()
result2 = pd.offsets.Day() + s
exp = klass([Timestamp('2000-01-16 00:15:00', tz='US/Central'),
Timestamp('2000-02-16', tz='US/Central')], name='a')
assert_func(result, exp)
assert_func(result2, exp)
s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
result = s + pd.offsets.MonthEnd()
result2 = pd.offsets.MonthEnd() + s
exp = klass([Timestamp('2000-01-31 00:15:00', tz='US/Central'),
Timestamp('2000-02-29', tz='US/Central')], name='a')
assert_func(result, exp)
assert_func(result2, exp)
Example #22
| Source File: test_arithmetic.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_shift_months(years, months):
s = DatetimeIndex([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31')])
actual = DatetimeIndex(shift_months(s.asi8, years * 12 + months))
raw = [x + pd.offsets.DateOffset(years=years, months=months)
for x in s]
expected = DatetimeIndex(raw)
tm.assert_index_equal(actual, expected)
Example #23
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_dt64arr_add_sub_offset_ndarray(self, tz_naive_fixture,
box_with_array):
# GH#18849
if box_with_array is pd.DataFrame:
pytest.xfail("FIXME: ValueError with transpose; "
"alignment error without")
tz = tz_naive_fixture
dti = pd.date_range('2017-01-01', periods=2, tz=tz)
dtarr = tm.box_expected(dti, box_with_array)
other = np.array([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
warn = None if box_with_array is pd.DataFrame else PerformanceWarning
with tm.assert_produces_warning(warn,
clear=[pd.core.arrays.datetimelike]):
res = dtarr + other
expected = DatetimeIndex([dti[n] + other[n] for n in range(len(dti))],
name=dti.name, freq='infer')
expected = tm.box_expected(expected, box_with_array)
tm.assert_equal(res, expected)
with tm.assert_produces_warning(warn,
clear=[pd.core.arrays.datetimelike]):
res2 = other + dtarr
tm.assert_equal(res2, expected)
with tm.assert_produces_warning(warn,
clear=[pd.core.arrays.datetimelike]):
res = dtarr - other
expected = DatetimeIndex([dti[n] - other[n] for n in range(len(dti))],
name=dti.name, freq='infer')
expected = tm.box_expected(expected, box_with_array)
tm.assert_equal(res, expected)
Example #24
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_dti_add_tick_tzaware(self, tz_aware_fixture, box_with_array):
# GH#21610, GH#22163 ensure DataFrame doesn't return object-dtype
tz = tz_aware_fixture
if tz == 'US/Pacific':
dates = date_range('2012-11-01', periods=3, tz=tz)
offset = dates + pd.offsets.Hour(5)
assert dates[0] + pd.offsets.Hour(5) == offset[0]
dates = date_range('2010-11-01 00:00',
periods=3, tz=tz, freq='H')
expected = DatetimeIndex(['2010-11-01 05:00', '2010-11-01 06:00',
'2010-11-01 07:00'], freq='H', tz=tz)
# FIXME: these raise ValueError with transpose=True
dates = tm.box_expected(dates, box_with_array, transpose=False)
expected = tm.box_expected(expected, box_with_array, transpose=False)
# TODO: parametrize over the scalar being added? radd? sub?
offset = dates + pd.offsets.Hour(5)
tm.assert_equal(offset, expected)
offset = dates + np.timedelta64(5, 'h')
tm.assert_equal(offset, expected)
offset = dates + timedelta(hours=5)
tm.assert_equal(offset, expected)
# -------------------------------------------------------------
# RelativeDelta DateOffsets
Example #25
| Source File: test_datetime64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_dt64arr_add_sub_tick_DateOffset_smoke(self, cls_name,
box_with_array):
# GH#4532
# smoke tests for valid DateOffsets
ser = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
ser = tm.box_expected(ser, box_with_array)
offset_cls = getattr(pd.offsets, cls_name)
ser + offset_cls(5)
offset_cls(5) + ser
ser - offset_cls(5)
Example #26
| Source File: test_operators.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_timedelta64_operations_with_DateOffset(self):
# GH 10699
td = Series([timedelta(minutes=5, seconds=3)] * 3)
result = td + pd.offsets.Minute(1)
expected = Series([timedelta(minutes=6, seconds=3)] * 3)
assert_series_equal(result, expected)
result = td - pd.offsets.Minute(1)
expected = Series([timedelta(minutes=4, seconds=3)] * 3)
assert_series_equal(result, expected)
with tm.assert_produces_warning(PerformanceWarning):
result = td + Series([pd.offsets.Minute(1), pd.offsets.Second(3),
pd.offsets.Hour(2)])
expected = Series([timedelta(minutes=6, seconds=3), timedelta(
minutes=5, seconds=6), timedelta(hours=2, minutes=5, seconds=3)])
assert_series_equal(result, expected)
result = td + pd.offsets.Minute(1) + pd.offsets.Second(12)
expected = Series([timedelta(minutes=6, seconds=15)] * 3)
assert_series_equal(result, expected)
# valid DateOffsets
for do in ['Hour', 'Minute', 'Second', 'Day', 'Micro', 'Milli',
'Nano']:
op = getattr(pd.offsets, do)
td + op(5)
op(5) + td
td - op(5)
op(5) - td
Example #27
| Source File: test_operators.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_dt64_series_sub_tick_DateOffset(self):
# GH 4532
# operate with pd.offsets
ser = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
expected = Series([Timestamp('20130101 9:00:55'),
Timestamp('20130101 9:01:55')])
result = ser - pd.offsets.Second(5)
assert_series_equal(result, expected)
result2 = -pd.offsets.Second(5) + ser
assert_series_equal(result2, expected)
with pytest.raises(TypeError):
pd.offsets.Second(5) - ser
Example #28
| Source File: test_operators.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_dt64_series_with_tick_DateOffset_smoke(self, cls_name):
# GH 4532
# smoke tests for valid DateOffsets
ser = Series([Timestamp('20130101 9:01'), Timestamp('20130101 9:02')])
offset_cls = getattr(pd.offsets, cls_name)
ser + offset_cls(5)
offset_cls(5) + ser
Example #29
| Source File: test_timedelta64.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_td64arr_sub_timedeltalike(self, two_hours, box):
# only test adding/sub offsets as - is now numeric
rng = timedelta_range('1 days', '10 days')
expected = timedelta_range('0 days 22:00:00', '9 days 22:00:00')
rng = tm.box_expected(rng, box)
expected = tm.box_expected(expected, box)
result = rng - two_hours
tm.assert_equal(result, expected)
# ------------------------------------------------------------------
# __add__/__sub__ with DateOffsets and arrays of DateOffsets
# TODO: this was taken from tests.series.test_operators; de-duplicate
Example #30
| Source File: test_ops.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_add_iadd(self):
for tz in self.tz:
# offset
offsets = [pd.offsets.Hour(2), timedelta(hours=2),
np.timedelta64(2, 'h'), Timedelta(hours=2)]
for delta in offsets:
rng = pd.date_range('2000-01-01', '2000-02-01', tz=tz)
result = rng + delta
expected = pd.date_range('2000-01-01 02:00',
'2000-02-01 02:00', tz=tz)
tm.assert_index_equal(result, expected)
rng += delta
tm.assert_index_equal(rng, expected)
# int
rng = pd.date_range('2000-01-01 09:00', freq='H', periods=10,
tz=tz)
result = rng + 1
expected = pd.date_range('2000-01-01 10:00', freq='H', periods=10,
tz=tz)
tm.assert_index_equal(result, expected)
rng += 1
tm.assert_index_equal(rng, expected)
idx = DatetimeIndex(['2011-01-01', '2011-01-02'])
msg = "cannot add DatetimeIndex and Timestamp"
with tm.assert_raises_regex(TypeError, msg):
idx + Timestamp('2011-01-01')
with tm.assert_raises_regex(TypeError, msg):
Timestamp('2011-01-01') + idx
