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from datetime import timedelta
from functools import partial
from operator import attrgetter
import dateutil
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs import OutOfBoundsDatetime, conversion
import pandas as pd
from pandas import (
DatetimeIndex, Index, Timestamp, date_range, datetime, offsets,
to_datetime)
from pandas.core.arrays import DatetimeArray, period_array
import pandas.util.testing as tm
class TestDatetimeIndex(object):
@pytest.mark.parametrize('dt_cls', [DatetimeIndex,
DatetimeArray._from_sequence])
def test_freq_validation_with_nat(self, dt_cls):
# GH#11587 make sure we get a useful error message when generate_range
# raises
msg = ("Inferred frequency None from passed values does not conform "
"to passed frequency D")
with pytest.raises(ValueError, match=msg):
dt_cls([pd.NaT, pd.Timestamp('2011-01-01')], freq='D')
with pytest.raises(ValueError, match=msg):
dt_cls([pd.NaT, pd.Timestamp('2011-01-01').value],
freq='D')
def test_categorical_preserves_tz(self):
# GH#18664 retain tz when going DTI-->Categorical-->DTI
# TODO: parametrize over DatetimeIndex/DatetimeArray
# once CategoricalIndex(DTA) works
dti = pd.DatetimeIndex(
[pd.NaT, '2015-01-01', '1999-04-06 15:14:13', '2015-01-01'],
tz='US/Eastern')
ci = pd.CategoricalIndex(dti)
carr = pd.Categorical(dti)
cser = pd.Series(ci)
for obj in [ci, carr, cser]:
result = pd.DatetimeIndex(obj)
tm.assert_index_equal(result, dti)
def test_dti_with_period_data_raises(self):
# GH#23675
data = pd.PeriodIndex(['2016Q1', '2016Q2'], freq='Q')
with pytest.raises(TypeError, match="PeriodDtype data is invalid"):
DatetimeIndex(data)
with pytest.raises(TypeError, match="PeriodDtype data is invalid"):
to_datetime(data)
with pytest.raises(TypeError, match="PeriodDtype data is invalid"):
DatetimeIndex(period_array(data))
with pytest.raises(TypeError, match="PeriodDtype data is invalid"):
to_datetime(period_array(data))
def test_dti_with_timedelta64_data_deprecation(self):
# GH#23675
data = np.array([0], dtype='m8[ns]')
with tm.assert_produces_warning(FutureWarning):
result = DatetimeIndex(data)
assert result[0] == Timestamp('1970-01-01')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = to_datetime(data)
assert result[0] == Timestamp('1970-01-01')
with tm.assert_produces_warning(FutureWarning):
result = DatetimeIndex(pd.TimedeltaIndex(data))
assert result[0] == Timestamp('1970-01-01')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = to_datetime(pd.TimedeltaIndex(data))
assert result[0] == Timestamp('1970-01-01')
def test_construction_caching(self):
df = pd.DataFrame({'dt': pd.date_range('20130101', periods=3),
'dttz': pd.date_range('20130101', periods=3,
tz='US/Eastern'),
'dt_with_null': [pd.Timestamp('20130101'), pd.NaT,
pd.Timestamp('20130103')],
'dtns': pd.date_range('20130101', periods=3,
freq='ns')})
assert df.dttz.dtype.tz.zone == 'US/Eastern'
@pytest.mark.parametrize('kwargs', [
{'tz': 'dtype.tz'},
{'dtype': 'dtype'},
{'dtype': 'dtype', 'tz': 'dtype.tz'}])
def test_construction_with_alt(self, kwargs, tz_aware_fixture):
tz = tz_aware_fixture
i = pd.date_range('20130101', periods=5, freq='H', tz=tz)
kwargs = {key: attrgetter(val)(i) for key, val in kwargs.items()}
result = DatetimeIndex(i, **kwargs)
tm.assert_index_equal(i, result)
@pytest.mark.parametrize('kwargs', [
{'tz': 'dtype.tz'},
{'dtype': 'dtype'},
{'dtype': 'dtype', 'tz': 'dtype.tz'}])
def test_construction_with_alt_tz_localize(self, kwargs, tz_aware_fixture):
tz = tz_aware_fixture
i = pd.date_range('20130101', periods=5, freq='H', tz=tz)
kwargs = {key: attrgetter(val)(i) for key, val in kwargs.items()}
if str(tz) in ('UTC', 'tzutc()'):
warn = None
else:
warn = FutureWarning
with tm.assert_produces_warning(warn, check_stacklevel=False):
result = DatetimeIndex(i.tz_localize(None).asi8, **kwargs)
expected = DatetimeIndex(i, **kwargs)
tm.assert_index_equal(result, expected)
# localize into the provided tz
i2 = DatetimeIndex(i.tz_localize(None).asi8, tz='UTC')
expected = i.tz_localize(None).tz_localize('UTC')
tm.assert_index_equal(i2, expected)
# incompat tz/dtype
pytest.raises(ValueError, lambda: DatetimeIndex(
i.tz_localize(None).asi8, dtype=i.dtype, tz='US/Pacific'))
def test_construction_index_with_mixed_timezones(self):
# gh-11488: no tz results in DatetimeIndex
result = Index([Timestamp('2011-01-01'),
Timestamp('2011-01-02')], name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01'),
Timestamp('2011-01-02')], name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is None
# same tz results in DatetimeIndex
result = Index([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='Asia/Tokyo')],
name='idx')
exp = DatetimeIndex(
[Timestamp('2011-01-01 10:00'), Timestamp('2011-01-02 10:00')
], tz='Asia/Tokyo', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
# same tz results in DatetimeIndex (DST)
result = Index([Timestamp('2011-01-01 10:00', tz='US/Eastern'),
Timestamp('2011-08-01 10:00', tz='US/Eastern')],
name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-08-01 10:00')],
tz='US/Eastern', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
# Different tz results in Index(dtype=object)
result = Index([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
name='idx')
exp = Index([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
dtype='object', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert not isinstance(result, DatetimeIndex)
result = Index([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
name='idx')
exp = Index([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
dtype='object', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert not isinstance(result, DatetimeIndex)
# length = 1
result = Index([Timestamp('2011-01-01')], name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01')], name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is None
# length = 1 with tz
result = Index(
[Timestamp('2011-01-01 10:00', tz='Asia/Tokyo')], name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 10:00')], tz='Asia/Tokyo',
name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
def test_construction_index_with_mixed_timezones_with_NaT(self):
# see gh-11488
result = Index([pd.NaT, Timestamp('2011-01-01'),
pd.NaT, Timestamp('2011-01-02')], name='idx')
exp = DatetimeIndex([pd.NaT, Timestamp('2011-01-01'),
pd.NaT, Timestamp('2011-01-02')], name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is None
# Same tz results in DatetimeIndex
result = Index([pd.NaT, Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
pd.NaT, Timestamp('2011-01-02 10:00',
tz='Asia/Tokyo')],
name='idx')
exp = DatetimeIndex([pd.NaT, Timestamp('2011-01-01 10:00'),
pd.NaT, Timestamp('2011-01-02 10:00')],
tz='Asia/Tokyo', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
# same tz results in DatetimeIndex (DST)
result = Index([Timestamp('2011-01-01 10:00', tz='US/Eastern'),
pd.NaT,
Timestamp('2011-08-01 10:00', tz='US/Eastern')],
name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 10:00'), pd.NaT,
Timestamp('2011-08-01 10:00')],
tz='US/Eastern', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
# different tz results in Index(dtype=object)
result = Index([pd.NaT, Timestamp('2011-01-01 10:00'),
pd.NaT, Timestamp('2011-01-02 10:00',
tz='US/Eastern')],
name='idx')
exp = Index([pd.NaT, Timestamp('2011-01-01 10:00'),
pd.NaT, Timestamp('2011-01-02 10:00', tz='US/Eastern')],
dtype='object', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert not isinstance(result, DatetimeIndex)
result = Index([pd.NaT, Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
pd.NaT, Timestamp('2011-01-02 10:00',
tz='US/Eastern')], name='idx')
exp = Index([pd.NaT, Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
pd.NaT, Timestamp('2011-01-02 10:00', tz='US/Eastern')],
dtype='object', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert not isinstance(result, DatetimeIndex)
# all NaT
result = Index([pd.NaT, pd.NaT], name='idx')
exp = DatetimeIndex([pd.NaT, pd.NaT], name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is None
# all NaT with tz
result = Index([pd.NaT, pd.NaT], tz='Asia/Tokyo', name='idx')
exp = DatetimeIndex([pd.NaT, pd.NaT], tz='Asia/Tokyo', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
assert result.tz is not None
assert result.tz == exp.tz
def test_construction_dti_with_mixed_timezones(self):
# GH 11488 (not changed, added explicit tests)
# no tz results in DatetimeIndex
result = DatetimeIndex(
[Timestamp('2011-01-01'), Timestamp('2011-01-02')], name='idx')
exp = DatetimeIndex(
[Timestamp('2011-01-01'), Timestamp('2011-01-02')], name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
# same tz results in DatetimeIndex
result = DatetimeIndex([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00',
tz='Asia/Tokyo')],
name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00')],
tz='Asia/Tokyo', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
# same tz results in DatetimeIndex (DST)
result = DatetimeIndex([Timestamp('2011-01-01 10:00', tz='US/Eastern'),
Timestamp('2011-08-01 10:00',
tz='US/Eastern')],
name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-08-01 10:00')],
tz='US/Eastern', name='idx')
tm.assert_index_equal(result, exp, exact=True)
assert isinstance(result, DatetimeIndex)
# tz mismatch affecting to tz-aware raises TypeError/ValueError
with pytest.raises(ValueError):
DatetimeIndex([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
name='idx')
msg = 'cannot be converted to datetime64'
with pytest.raises(ValueError, match=msg):
DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
tz='Asia/Tokyo', name='idx')
with pytest.raises(ValueError):
DatetimeIndex([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
tz='US/Eastern', name='idx')
with pytest.raises(ValueError, match=msg):
# passing tz should results in DatetimeIndex, then mismatch raises
# TypeError
Index([pd.NaT, Timestamp('2011-01-01 10:00'),
pd.NaT, Timestamp('2011-01-02 10:00', tz='US/Eastern')],
tz='Asia/Tokyo', name='idx')
def test_construction_base_constructor(self):
arr = [pd.Timestamp('2011-01-01'), pd.NaT, pd.Timestamp('2011-01-03')]
tm.assert_index_equal(pd.Index(arr), pd.DatetimeIndex(arr))
tm.assert_index_equal(pd.Index(np.array(arr)),
pd.DatetimeIndex(np.array(arr)))
arr = [np.nan, pd.NaT, pd.Timestamp('2011-01-03')]
tm.assert_index_equal(pd.Index(arr), pd.DatetimeIndex(arr))
tm.assert_index_equal(pd.Index(np.array(arr)),
pd.DatetimeIndex(np.array(arr)))
def test_construction_outofbounds(self):
# GH 13663
dates = [datetime(3000, 1, 1), datetime(4000, 1, 1),
datetime(5000, 1, 1), datetime(6000, 1, 1)]
exp = Index(dates, dtype=object)
# coerces to object
tm.assert_index_equal(Index(dates), exp)
with pytest.raises(OutOfBoundsDatetime):
# can't create DatetimeIndex
DatetimeIndex(dates)
def test_construction_with_ndarray(self):
# GH 5152
dates = [datetime(2013, 10, 7),
datetime(2013, 10, 8),
datetime(2013, 10, 9)]
data = DatetimeIndex(dates, freq=pd.offsets.BDay()).values
result = DatetimeIndex(data, freq=pd.offsets.BDay())
expected = DatetimeIndex(['2013-10-07',
'2013-10-08',
'2013-10-09'],
freq='B')
tm.assert_index_equal(result, expected)
def test_verify_integrity_deprecated(self):
# GH#23919
with tm.assert_produces_warning(FutureWarning):
DatetimeIndex(['1/1/2000'], verify_integrity=False)
def test_range_kwargs_deprecated(self):
# GH#23919
with tm.assert_produces_warning(FutureWarning):
DatetimeIndex(start='1/1/2000', end='1/10/2000', freq='D')
def test_integer_values_and_tz_deprecated(self):
# GH-24559
values = np.array([946684800000000000])
with tm.assert_produces_warning(FutureWarning):
result = DatetimeIndex(values, tz='US/Central')
expected = pd.DatetimeIndex(['2000-01-01T00:00:00'], tz="US/Central")
tm.assert_index_equal(result, expected)
# but UTC is *not* deprecated.
with tm.assert_produces_warning(None):
result = DatetimeIndex(values, tz='UTC')
expected = pd.DatetimeIndex(['2000-01-01T00:00:00'], tz="US/Central")
def test_constructor_coverage(self):
rng = date_range('1/1/2000', periods=10.5)
exp = date_range('1/1/2000', periods=10)
tm.assert_index_equal(rng, exp)
msg = 'periods must be a number, got foo'
with pytest.raises(TypeError, match=msg):
date_range(start='1/1/2000', periods='foo', freq='D')
with pytest.raises(ValueError):
with tm.assert_produces_warning(FutureWarning):
DatetimeIndex(start='1/1/2000', end='1/10/2000')
with pytest.raises(TypeError):
DatetimeIndex('1/1/2000')
# generator expression
gen = (datetime(2000, 1, 1) + timedelta(i) for i in range(10))
result = DatetimeIndex(gen)
expected = DatetimeIndex([datetime(2000, 1, 1) + timedelta(i)
for i in range(10)])
tm.assert_index_equal(result, expected)
# NumPy string array
strings = np.array(['2000-01-01', '2000-01-02', '2000-01-03'])
result = DatetimeIndex(strings)
expected = DatetimeIndex(strings.astype('O'))
tm.assert_index_equal(result, expected)
from_ints = DatetimeIndex(expected.asi8)
tm.assert_index_equal(from_ints, expected)
# string with NaT
strings = np.array(['2000-01-01', '2000-01-02', 'NaT'])
result = DatetimeIndex(strings)
expected = DatetimeIndex(strings.astype('O'))
tm.assert_index_equal(result, expected)
from_ints = DatetimeIndex(expected.asi8)
tm.assert_index_equal(from_ints, expected)
# non-conforming
pytest.raises(ValueError, DatetimeIndex,
['2000-01-01', '2000-01-02', '2000-01-04'], freq='D')
pytest.raises(ValueError, date_range, start='2011-01-01',
freq='b')
pytest.raises(ValueError, date_range, end='2011-01-01',
freq='B')
pytest.raises(ValueError, date_range, periods=10, freq='D')
@pytest.mark.parametrize('freq', ['AS', 'W-SUN'])
def test_constructor_datetime64_tzformat(self, freq):
# see GH#6572: ISO 8601 format results in pytz.FixedOffset
idx = date_range('2013-01-01T00:00:00-05:00',
'2016-01-01T23:59:59-05:00', freq=freq)
expected = date_range('2013-01-01T00:00:00', '2016-01-01T23:59:59',
freq=freq, tz=pytz.FixedOffset(-300))
tm.assert_index_equal(idx, expected)
# Unable to use `US/Eastern` because of DST
expected_i8 = date_range('2013-01-01T00:00:00',
'2016-01-01T23:59:59', freq=freq,
tz='America/Lima')
tm.assert_numpy_array_equal(idx.asi8, expected_i8.asi8)
idx = date_range('2013-01-01T00:00:00+09:00',
'2016-01-01T23:59:59+09:00', freq=freq)
expected = date_range('2013-01-01T00:00:00', '2016-01-01T23:59:59',
freq=freq, tz=pytz.FixedOffset(540))
tm.assert_index_equal(idx, expected)
expected_i8 = date_range('2013-01-01T00:00:00',
'2016-01-01T23:59:59', freq=freq,
tz='Asia/Tokyo')
tm.assert_numpy_array_equal(idx.asi8, expected_i8.asi8)
# Non ISO 8601 format results in dateutil.tz.tzoffset
idx = date_range('2013/1/1 0:00:00-5:00', '2016/1/1 23:59:59-5:00',
freq=freq)
expected = date_range('2013-01-01T00:00:00', '2016-01-01T23:59:59',
freq=freq, tz=pytz.FixedOffset(-300))
tm.assert_index_equal(idx, expected)
# Unable to use `US/Eastern` because of DST
expected_i8 = date_range('2013-01-01T00:00:00',
'2016-01-01T23:59:59', freq=freq,
tz='America/Lima')
tm.assert_numpy_array_equal(idx.asi8, expected_i8.asi8)
idx = date_range('2013/1/1 0:00:00+9:00',
'2016/1/1 23:59:59+09:00', freq=freq)
expected = date_range('2013-01-01T00:00:00', '2016-01-01T23:59:59',
freq=freq, tz=pytz.FixedOffset(540))
tm.assert_index_equal(idx, expected)
expected_i8 = date_range('2013-01-01T00:00:00',
'2016-01-01T23:59:59', freq=freq,
tz='Asia/Tokyo')
tm.assert_numpy_array_equal(idx.asi8, expected_i8.asi8)
def test_constructor_dtype(self):
# passing a dtype with a tz should localize
idx = DatetimeIndex(['2013-01-01', '2013-01-02'],
dtype='datetime64[ns, US/Eastern]')
expected = DatetimeIndex(['2013-01-01', '2013-01-02']
).tz_localize('US/Eastern')
tm.assert_index_equal(idx, expected)
idx = DatetimeIndex(['2013-01-01', '2013-01-02'],
tz='US/Eastern')
tm.assert_index_equal(idx, expected)
# if we already have a tz and its not the same, then raise
idx = DatetimeIndex(['2013-01-01', '2013-01-02'],
dtype='datetime64[ns, US/Eastern]')
pytest.raises(ValueError,
lambda: DatetimeIndex(idx,
dtype='datetime64[ns]'))
# this is effectively trying to convert tz's
pytest.raises(TypeError,
lambda: DatetimeIndex(idx,
dtype='datetime64[ns, CET]'))
pytest.raises(ValueError,
lambda: DatetimeIndex(
idx, tz='CET',
dtype='datetime64[ns, US/Eastern]'))
result = DatetimeIndex(idx, dtype='datetime64[ns, US/Eastern]')
tm.assert_index_equal(idx, result)
def test_constructor_name(self):
idx = date_range(start='2000-01-01', periods=1, freq='A',
name='TEST')
assert idx.name == 'TEST'
def test_000constructor_resolution(self):
# 2252
t1 = Timestamp((1352934390 * 1000000000) + 1000000 + 1000 + 1)
idx = DatetimeIndex([t1])
assert idx.nanosecond[0] == t1.nanosecond
def test_disallow_setting_tz(self):
# GH 3746
dti = DatetimeIndex(['2010'], tz='UTC')
with pytest.raises(AttributeError):
dti.tz = pytz.timezone('US/Pacific')
@pytest.mark.parametrize('tz', [
None, 'America/Los_Angeles', pytz.timezone('America/Los_Angeles'),
Timestamp('2000', tz='America/Los_Angeles').tz])
def test_constructor_start_end_with_tz(self, tz):
# GH 18595
start = Timestamp('2013-01-01 06:00:00', tz='America/Los_Angeles')
end = Timestamp('2013-01-02 06:00:00', tz='America/Los_Angeles')
result = date_range(freq='D', start=start, end=end, tz=tz)
expected = DatetimeIndex(['2013-01-01 06:00:00',
'2013-01-02 06:00:00'],
tz='America/Los_Angeles')
tm.assert_index_equal(result, expected)
# Especially assert that the timezone is consistent for pytz
assert pytz.timezone('America/Los_Angeles') is result.tz
@pytest.mark.parametrize('tz', ['US/Pacific', 'US/Eastern', 'Asia/Tokyo'])
def test_constructor_with_non_normalized_pytz(self, tz):
# GH 18595
non_norm_tz = Timestamp('2010', tz=tz).tz
result = DatetimeIndex(['2010'], tz=non_norm_tz)
assert pytz.timezone(tz) is result.tz
def test_constructor_timestamp_near_dst(self):
# GH 20854
ts = [Timestamp('2016-10-30 03:00:00+0300', tz='Europe/Helsinki'),
Timestamp('2016-10-30 03:00:00+0200', tz='Europe/Helsinki')]
result = DatetimeIndex(ts)
expected = DatetimeIndex([ts[0].to_pydatetime(),
ts[1].to_pydatetime()])
tm.assert_index_equal(result, expected)
# TODO(GH-24559): Remove the xfail for the tz-aware case.
@pytest.mark.parametrize('klass', [Index, DatetimeIndex])
@pytest.mark.parametrize('box', [
np.array, partial(np.array, dtype=object), list])
@pytest.mark.parametrize('tz, dtype', [
pytest.param('US/Pacific', 'datetime64[ns, US/Pacific]',
marks=[pytest.mark.xfail(),
pytest.mark.filterwarnings(
"ignore:\\n Passing:FutureWarning")]),
[None, 'datetime64[ns]'],
])
def test_constructor_with_int_tz(self, klass, box, tz, dtype):
# GH 20997, 20964
ts = Timestamp('2018-01-01', tz=tz)
result = klass(box([ts.value]), dtype=dtype)
expected = klass([ts])
assert result == expected
# This is the desired future behavior
@pytest.mark.xfail(reason="Future behavior", strict=False)
@pytest.mark.filterwarnings("ignore:\\n Passing:FutureWarning")
def test_construction_int_rountrip(self, tz_naive_fixture):
# GH 12619
# TODO(GH-24559): Remove xfail
tz = tz_naive_fixture
result = 1293858000000000000
expected = DatetimeIndex([1293858000000000000], tz=tz).asi8[0]
assert result == expected
def test_construction_from_replaced_timestamps_with_dst(self):
# GH 18785
index = pd.date_range(pd.Timestamp(2000, 1, 1),
pd.Timestamp(2005, 1, 1),
freq='MS', tz='Australia/Melbourne')
test = pd.DataFrame({'data': range(len(index))}, index=index)
test = test.resample('Y').mean()
result = pd.DatetimeIndex([x.replace(month=6, day=1)
for x in test.index])
expected = pd.DatetimeIndex(['2000-06-01 00:00:00',
'2001-06-01 00:00:00',
'2002-06-01 00:00:00',
'2003-06-01 00:00:00',
'2004-06-01 00:00:00',
'2005-06-01 00:00:00'],
tz='Australia/Melbourne')
tm.assert_index_equal(result, expected)
def test_construction_with_tz_and_tz_aware_dti(self):
# GH 23579
dti = date_range('2016-01-01', periods=3, tz='US/Central')
with pytest.raises(TypeError):
DatetimeIndex(dti, tz='Asia/Tokyo')
def test_construction_with_nat_and_tzlocal(self):
tz = dateutil.tz.tzlocal()
result = DatetimeIndex(['2018', 'NaT'], tz=tz)
expected = DatetimeIndex([Timestamp('2018', tz=tz), pd.NaT])
tm.assert_index_equal(result, expected)
def test_constructor_no_precision_warns(self):
# GH-24753, GH-24739
expected = pd.DatetimeIndex(['2000'], dtype='datetime64[ns]')
# we set the stacklevel for DatetimeIndex
with tm.assert_produces_warning(FutureWarning):
result = pd.DatetimeIndex(['2000'], dtype='datetime64')
tm.assert_index_equal(result, expected)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = pd.Index(['2000'], dtype='datetime64')
tm.assert_index_equal(result, expected)
def test_constructor_wrong_precision_raises(self):
with pytest.raises(ValueError):
pd.DatetimeIndex(['2000'], dtype='datetime64[us]')
class TestTimeSeries(object):
def test_dti_constructor_preserve_dti_freq(self):
rng = date_range('1/1/2000', '1/2/2000', freq='5min')
rng2 = DatetimeIndex(rng)
assert rng.freq == rng2.freq
def test_dti_constructor_years_only(self, tz_naive_fixture):
tz = tz_naive_fixture
# GH 6961
rng1 = date_range('2014', '2015', freq='M', tz=tz)
expected1 = date_range('2014-01-31', '2014-12-31', freq='M', tz=tz)
rng2 = date_range('2014', '2015', freq='MS', tz=tz)
expected2 = date_range('2014-01-01', '2015-01-01', freq='MS', tz=tz)
rng3 = date_range('2014', '2020', freq='A', tz=tz)
expected3 = date_range('2014-12-31', '2019-12-31', freq='A', tz=tz)
rng4 = date_range('2014', '2020', freq='AS', tz=tz)
expected4 = date_range('2014-01-01', '2020-01-01', freq='AS', tz=tz)
for rng, expected in [(rng1, expected1), (rng2, expected2),
(rng3, expected3), (rng4, expected4)]:
tm.assert_index_equal(rng, expected)
def test_dti_constructor_small_int(self, any_int_dtype):
# see gh-13721
exp = DatetimeIndex(['1970-01-01 00:00:00.00000000',
'1970-01-01 00:00:00.00000001',
'1970-01-01 00:00:00.00000002'])
arr = np.array([0, 10, 20], dtype=any_int_dtype)
tm.assert_index_equal(DatetimeIndex(arr), exp)
def test_ctor_str_intraday(self):
rng = DatetimeIndex(['1-1-2000 00:00:01'])
assert rng[0].second == 1
def test_is_(self):
dti = date_range(start='1/1/2005', end='12/1/2005', freq='M')
assert dti.is_(dti)
assert dti.is_(dti.view())
assert not dti.is_(dti.copy())
def test_index_cast_datetime64_other_units(self):
arr = np.arange(0, 100, 10, dtype=np.int64).view('M8[D]')
idx = Index(arr)
assert (idx.values == conversion.ensure_datetime64ns(arr)).all()
def test_constructor_int64_nocopy(self):
# GH#1624
arr = np.arange(1000, dtype=np.int64)
index = DatetimeIndex(arr)
arr[50:100] = -1
assert (index.asi8[50:100] == -1).all()
arr = np.arange(1000, dtype=np.int64)
index = DatetimeIndex(arr, copy=True)
arr[50:100] = -1
assert (index.asi8[50:100] != -1).all()
@pytest.mark.parametrize('freq', ['M', 'Q', 'A', 'D', 'B', 'BH',
'T', 'S', 'L', 'U', 'H', 'N', 'C'])
def test_from_freq_recreate_from_data(self, freq):
org = date_range(start='2001/02/01 09:00', freq=freq, periods=1)
idx = DatetimeIndex(org, freq=freq)
tm.assert_index_equal(idx, org)
org = date_range(start='2001/02/01 09:00', freq=freq,
tz='US/Pacific', periods=1)
idx = DatetimeIndex(org, freq=freq, tz='US/Pacific')
tm.assert_index_equal(idx, org)
def test_datetimeindex_constructor_misc(self):
arr = ['1/1/2005', '1/2/2005', 'Jn 3, 2005', '2005-01-04']
pytest.raises(Exception, DatetimeIndex, arr)
arr = ['1/1/2005', '1/2/2005', '1/3/2005', '2005-01-04']
idx1 = DatetimeIndex(arr)
arr = [datetime(2005, 1, 1), '1/2/2005', '1/3/2005', '2005-01-04']
idx2 = DatetimeIndex(arr)
arr = [Timestamp(datetime(2005, 1, 1)), '1/2/2005', '1/3/2005',
'2005-01-04']
idx3 = DatetimeIndex(arr)
arr = np.array(['1/1/2005', '1/2/2005', '1/3/2005',
'2005-01-04'], dtype='O')
idx4 = DatetimeIndex(arr)
arr = to_datetime(['1/1/2005', '1/2/2005', '1/3/2005', '2005-01-04'])
idx5 = DatetimeIndex(arr)
arr = to_datetime(['1/1/2005', '1/2/2005', 'Jan 3, 2005', '2005-01-04'
])
idx6 = DatetimeIndex(arr)
idx7 = DatetimeIndex(['12/05/2007', '25/01/2008'], dayfirst=True)
idx8 = DatetimeIndex(['2007/05/12', '2008/01/25'], dayfirst=False,
yearfirst=True)
tm.assert_index_equal(idx7, idx8)
for other in [idx2, idx3, idx4, idx5, idx6]:
assert (idx1.values == other.values).all()
sdate = datetime(1999, 12, 25)
edate = datetime(2000, 1, 1)
idx = date_range(start=sdate, freq='1B', periods=20)
assert len(idx) == 20
assert idx[0] == sdate + 0 * offsets.BDay()
assert idx.freq == 'B'
idx = date_range(end=edate, freq=('D', 5), periods=20)
assert len(idx) == 20
assert idx[-1] == edate
assert idx.freq == '5D'
idx1 = date_range(start=sdate, end=edate, freq='W-SUN')
idx2 = date_range(start=sdate, end=edate,
freq=offsets.Week(weekday=6))
assert len(idx1) == len(idx2)
assert idx1.freq == idx2.freq
idx1 = date_range(start=sdate, end=edate, freq='QS')
idx2 = date_range(start=sdate, end=edate,
freq=offsets.QuarterBegin(startingMonth=1))
assert len(idx1) == len(idx2)
assert idx1.freq == idx2.freq
idx1 = date_range(start=sdate, end=edate, freq='BQ')
idx2 = date_range(start=sdate, end=edate,
freq=offsets.BQuarterEnd(startingMonth=12))
assert len(idx1) == len(idx2)
assert idx1.freq == idx2.freq