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test_datetimelike.py
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# -*- coding: utf-8 -*-
from datetime import timedelta, time
import numpy as np
from pandas import (DatetimeIndex, Float64Index, Index, Int64Index,
NaT, Period, PeriodIndex, Series, Timedelta,
TimedeltaIndex, date_range, period_range,
timedelta_range, notnull)
import pandas.util.testing as tm
import pandas as pd
from pandas.lib import Timestamp
from .common import Base
class DatetimeLike(Base):
def test_shift_identity(self):
idx = self.create_index()
self.assert_index_equal(idx, idx.shift(0))
def test_str(self):
# test the string repr
idx = self.create_index()
idx.name = 'foo'
self.assertFalse("length=%s" % len(idx) in str(idx))
self.assertTrue("'foo'" in str(idx))
self.assertTrue(idx.__class__.__name__ in str(idx))
if hasattr(idx, 'tz'):
if idx.tz is not None:
self.assertTrue(idx.tz in str(idx))
if hasattr(idx, 'freq'):
self.assertTrue("freq='%s'" % idx.freqstr in str(idx))
def test_view(self):
super(DatetimeLike, self).test_view()
i = self.create_index()
i_view = i.view('i8')
result = self._holder(i)
tm.assert_index_equal(result, i)
i_view = i.view(self._holder)
result = self._holder(i)
tm.assert_index_equal(result, i_view)
class TestDatetimeIndex(DatetimeLike, tm.TestCase):
_holder = DatetimeIndex
_multiprocess_can_split_ = True
def setUp(self):
self.indices = dict(index=tm.makeDateIndex(10))
self.setup_indices()
def create_index(self):
return date_range('20130101', periods=5)
def test_shift(self):
# test shift for datetimeIndex and non datetimeIndex
# GH8083
drange = self.create_index()
result = drange.shift(1)
expected = DatetimeIndex(['2013-01-02', '2013-01-03', '2013-01-04',
'2013-01-05',
'2013-01-06'], freq='D')
self.assert_index_equal(result, expected)
result = drange.shift(-1)
expected = DatetimeIndex(['2012-12-31', '2013-01-01', '2013-01-02',
'2013-01-03', '2013-01-04'],
freq='D')
self.assert_index_equal(result, expected)
result = drange.shift(3, freq='2D')
expected = DatetimeIndex(['2013-01-07', '2013-01-08', '2013-01-09',
'2013-01-10',
'2013-01-11'], freq='D')
self.assert_index_equal(result, expected)
def test_construction_with_alt(self):
i = pd.date_range('20130101', periods=5, freq='H', tz='US/Eastern')
i2 = DatetimeIndex(i, dtype=i.dtype)
self.assert_index_equal(i, i2)
i2 = DatetimeIndex(i.tz_localize(None).asi8, tz=i.dtype.tz)
self.assert_index_equal(i, i2)
i2 = DatetimeIndex(i.tz_localize(None).asi8, dtype=i.dtype)
self.assert_index_equal(i, i2)
i2 = DatetimeIndex(
i.tz_localize(None).asi8, dtype=i.dtype, tz=i.dtype.tz)
self.assert_index_equal(i, i2)
# localize into the provided tz
i2 = DatetimeIndex(i.tz_localize(None).asi8, tz='UTC')
expected = i.tz_localize(None).tz_localize('UTC')
self.assert_index_equal(i2, expected)
# incompat tz/dtype
self.assertRaises(ValueError, lambda: DatetimeIndex(
i.tz_localize(None).asi8, dtype=i.dtype, tz='US/Pacific'))
def test_pickle_compat_construction(self):
pass
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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNone(result.tz)
# 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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(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')
self.assert_index_equal(result, exp, exact=True)
self.assertFalse(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')
self.assert_index_equal(result, exp, exact=True)
self.assertFalse(isinstance(result, DatetimeIndex))
# passing tz results in DatetimeIndex
result = Index([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
tz='Asia/Tokyo', name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 19:00'),
Timestamp('2011-01-03 00:00')],
tz='Asia/Tokyo', name='idx')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
# length = 1
result = Index([Timestamp('2011-01-01')], name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01')], name='idx')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNone(result.tz)
# 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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(result.tz, exp.tz)
def test_construction_index_with_mixed_timezones_with_NaT(self):
# 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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNone(result.tz)
# 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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(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')
self.assert_index_equal(result, exp, exact=True)
self.assertFalse(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')
self.assert_index_equal(result, exp, exact=True)
self.assertFalse(isinstance(result, DatetimeIndex))
# passing tz results in DatetimeIndex
result = 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')
exp = DatetimeIndex([pd.NaT, Timestamp('2011-01-01 19:00'),
pd.NaT, Timestamp('2011-01-03 00:00')],
tz='Asia/Tokyo', name='idx')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
# all NaT
result = Index([pd.NaT, pd.NaT], name='idx')
exp = DatetimeIndex([pd.NaT, pd.NaT], name='idx')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNone(result.tz)
# 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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
self.assertIsNotNone(result.tz)
self.assertEqual(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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(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')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
# different tz coerces tz-naive to tz-awareIndex(dtype=object)
result = DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00',
tz='US/Eastern')], name='idx')
exp = DatetimeIndex([Timestamp('2011-01-01 05:00'),
Timestamp('2011-01-02 10:00')],
tz='US/Eastern', name='idx')
self.assert_index_equal(result, exp, exact=True)
self.assertTrue(isinstance(result, DatetimeIndex))
# tz mismatch affecting to tz-aware raises TypeError/ValueError
with tm.assertRaises(ValueError):
DatetimeIndex([Timestamp('2011-01-01 10:00', tz='Asia/Tokyo'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
name='idx')
with tm.assertRaises(TypeError):
DatetimeIndex([Timestamp('2011-01-01 10:00'),
Timestamp('2011-01-02 10:00', tz='US/Eastern')],
tz='Asia/Tokyo', name='idx')
with tm.assertRaises(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')
def test_astype(self):
# GH 13149, GH 13209
idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])
result = idx.astype(object)
expected = Index([Timestamp('2016-05-16')] + [NaT] * 3, dtype=object)
tm.assert_index_equal(result, expected)
result = idx.astype(int)
expected = Int64Index([1463356800000000000] +
[-9223372036854775808] * 3, dtype=np.int64)
tm.assert_index_equal(result, expected)
rng = date_range('1/1/2000', periods=10)
result = rng.astype('i8')
self.assert_index_equal(result, Index(rng.asi8))
self.assert_numpy_array_equal(result.values, rng.asi8)
def test_astype_with_tz(self):
# with tz
rng = date_range('1/1/2000', periods=10, tz='US/Eastern')
result = rng.astype('datetime64[ns]')
expected = (date_range('1/1/2000', periods=10,
tz='US/Eastern')
.tz_convert('UTC').tz_localize(None))
tm.assert_index_equal(result, expected)
# BUG#10442 : testing astype(str) is correct for Series/DatetimeIndex
result = pd.Series(pd.date_range('2012-01-01', periods=3)).astype(str)
expected = pd.Series(
['2012-01-01', '2012-01-02', '2012-01-03'], dtype=object)
tm.assert_series_equal(result, expected)
result = Series(pd.date_range('2012-01-01', periods=3,
tz='US/Eastern')).astype(str)
expected = Series(['2012-01-01 00:00:00-05:00',
'2012-01-02 00:00:00-05:00',
'2012-01-03 00:00:00-05:00'],
dtype=object)
tm.assert_series_equal(result, expected)
def test_astype_str_compat(self):
# GH 13149, GH 13209
# verify that we are returing NaT as a string (and not unicode)
idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])
result = idx.astype(str)
expected = Index(['2016-05-16', 'NaT', 'NaT', 'NaT'], dtype=object)
tm.assert_index_equal(result, expected)
def test_astype_str(self):
# test astype string - #10442
result = date_range('2012-01-01', periods=4,
name='test_name').astype(str)
expected = Index(['2012-01-01', '2012-01-02', '2012-01-03',
'2012-01-04'], name='test_name', dtype=object)
tm.assert_index_equal(result, expected)
# test astype string with tz and name
result = date_range('2012-01-01', periods=3, name='test_name',
tz='US/Eastern').astype(str)
expected = Index(['2012-01-01 00:00:00-05:00',
'2012-01-02 00:00:00-05:00',
'2012-01-03 00:00:00-05:00'],
name='test_name', dtype=object)
tm.assert_index_equal(result, expected)
# test astype string with freqH and name
result = date_range('1/1/2011', periods=3, freq='H',
name='test_name').astype(str)
expected = Index(['2011-01-01 00:00:00', '2011-01-01 01:00:00',
'2011-01-01 02:00:00'],
name='test_name', dtype=object)
tm.assert_index_equal(result, expected)
# test astype string with freqH and timezone
result = date_range('3/6/2012 00:00', periods=2, freq='H',
tz='Europe/London', name='test_name').astype(str)
expected = Index(['2012-03-06 00:00:00+00:00',
'2012-03-06 01:00:00+00:00'],
dtype=object, name='test_name')
tm.assert_index_equal(result, expected)
def test_astype_datetime64(self):
# GH 13149, GH 13209
idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])
result = idx.astype('datetime64[ns]')
tm.assert_index_equal(result, idx)
self.assertFalse(result is idx)
result = idx.astype('datetime64[ns]', copy=False)
tm.assert_index_equal(result, idx)
self.assertTrue(result is idx)
idx_tz = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN], tz='EST')
result = idx_tz.astype('datetime64[ns]')
expected = DatetimeIndex(['2016-05-16 05:00:00', 'NaT', 'NaT', 'NaT'],
dtype='datetime64[ns]')
tm.assert_index_equal(result, expected)
def test_astype_raises(self):
# GH 13149, GH 13209
idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])
self.assertRaises(ValueError, idx.astype, float)
self.assertRaises(ValueError, idx.astype, 'timedelta64')
self.assertRaises(ValueError, idx.astype, 'timedelta64[ns]')
self.assertRaises(ValueError, idx.astype, 'datetime64')
self.assertRaises(ValueError, idx.astype, 'datetime64[D]')
def test_where_other(self):
# other is ndarray or Index
i = pd.date_range('20130101', periods=3, tz='US/Eastern')
for arr in [np.nan, pd.NaT]:
result = i.where(notnull(i), other=np.nan)
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notnull(i2), i2)
tm.assert_index_equal(result, i2)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notnull(i2), i2.values)
tm.assert_index_equal(result, i2)
def test_where_tz(self):
i = pd.date_range('20130101', periods=3, tz='US/Eastern')
result = i.where(notnull(i))
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notnull(i2))
expected = i2
tm.assert_index_equal(result, expected)
def test_get_loc(self):
idx = pd.date_range('2000-01-01', periods=3)
for method in [None, 'pad', 'backfill', 'nearest']:
self.assertEqual(idx.get_loc(idx[1], method), 1)
self.assertEqual(idx.get_loc(idx[1].to_pydatetime(), method), 1)
self.assertEqual(idx.get_loc(str(idx[1]), method), 1)
if method is not None:
self.assertEqual(idx.get_loc(idx[1], method,
tolerance=pd.Timedelta('0 days')),
1)
self.assertEqual(idx.get_loc('2000-01-01', method='nearest'), 0)
self.assertEqual(idx.get_loc('2000-01-01T12', method='nearest'), 1)
self.assertEqual(idx.get_loc('2000-01-01T12', method='nearest',
tolerance='1 day'), 1)
self.assertEqual(idx.get_loc('2000-01-01T12', method='nearest',
tolerance=pd.Timedelta('1D')), 1)
self.assertEqual(idx.get_loc('2000-01-01T12', method='nearest',
tolerance=np.timedelta64(1, 'D')), 1)
self.assertEqual(idx.get_loc('2000-01-01T12', method='nearest',
tolerance=timedelta(1)), 1)
with tm.assertRaisesRegexp(ValueError, 'must be convertible'):
idx.get_loc('2000-01-01T12', method='nearest', tolerance='foo')
with tm.assertRaises(KeyError):
idx.get_loc('2000-01-01T03', method='nearest', tolerance='2 hours')
self.assertEqual(idx.get_loc('2000', method='nearest'), slice(0, 3))
self.assertEqual(idx.get_loc('2000-01', method='nearest'), slice(0, 3))
self.assertEqual(idx.get_loc('1999', method='nearest'), 0)
self.assertEqual(idx.get_loc('2001', method='nearest'), 2)
with tm.assertRaises(KeyError):
idx.get_loc('1999', method='pad')
with tm.assertRaises(KeyError):
idx.get_loc('2001', method='backfill')
with tm.assertRaises(KeyError):
idx.get_loc('foobar')
with tm.assertRaises(TypeError):
idx.get_loc(slice(2))
idx = pd.to_datetime(['2000-01-01', '2000-01-04'])
self.assertEqual(idx.get_loc('2000-01-02', method='nearest'), 0)
self.assertEqual(idx.get_loc('2000-01-03', method='nearest'), 1)
self.assertEqual(idx.get_loc('2000-01', method='nearest'), slice(0, 2))
# time indexing
idx = pd.date_range('2000-01-01', periods=24, freq='H')
tm.assert_numpy_array_equal(idx.get_loc(time(12)),
np.array([12], dtype=np.int64))
tm.assert_numpy_array_equal(idx.get_loc(time(12, 30)),
np.array([], dtype=np.int64))
with tm.assertRaises(NotImplementedError):
idx.get_loc(time(12, 30), method='pad')
def test_get_indexer(self):
idx = pd.date_range('2000-01-01', periods=3)
tm.assert_numpy_array_equal(idx.get_indexer(idx), np.array([0, 1, 2]))
target = idx[0] + pd.to_timedelta(['-1 hour', '12 hours',
'1 day 1 hour'])
tm.assert_numpy_array_equal(idx.get_indexer(target, 'pad'),
np.array([-1, 0, 1]))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'backfill'),
np.array([0, 1, 2]))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest'),
np.array([0, 1, 1]))
tm.assert_numpy_array_equal(
idx.get_indexer(target, 'nearest',
tolerance=pd.Timedelta('1 hour')),
np.array([0, -1, 1]))
with tm.assertRaises(ValueError):
idx.get_indexer(idx[[0]], method='nearest', tolerance='foo')
def test_roundtrip_pickle_with_tz(self):
# GH 8367
# round-trip of timezone
index = date_range('20130101', periods=3, tz='US/Eastern', name='foo')
unpickled = self.round_trip_pickle(index)
self.assert_index_equal(index, unpickled)
def test_reindex_preserves_tz_if_target_is_empty_list_or_array(self):
# GH7774
index = date_range('20130101', periods=3, tz='US/Eastern')
self.assertEqual(str(index.reindex([])[0].tz), 'US/Eastern')
self.assertEqual(str(index.reindex(np.array([]))[0].tz), 'US/Eastern')
def test_time_loc(self): # GH8667
from datetime import time
from pandas.index import _SIZE_CUTOFF
ns = _SIZE_CUTOFF + np.array([-100, 100], dtype=np.int64)
key = time(15, 11, 30)
start = key.hour * 3600 + key.minute * 60 + key.second
step = 24 * 3600
for n in ns:
idx = pd.date_range('2014-11-26', periods=n, freq='S')
ts = pd.Series(np.random.randn(n), index=idx)
i = np.arange(start, n, step)
tm.assert_numpy_array_equal(ts.index.get_loc(key), i)
tm.assert_series_equal(ts[key], ts.iloc[i])
left, right = ts.copy(), ts.copy()
left[key] *= -10
right.iloc[i] *= -10
tm.assert_series_equal(left, right)
def test_time_overflow_for_32bit_machines(self):
# GH8943. On some machines NumPy defaults to np.int32 (for example,
# 32-bit Linux machines). In the function _generate_regular_range
# found in tseries/index.py, `periods` gets multiplied by `strides`
# (which has value 1e9) and since the max value for np.int32 is ~2e9,
# and since those machines won't promote np.int32 to np.int64, we get
# overflow.
periods = np.int_(1000)
idx1 = pd.date_range(start='2000', periods=periods, freq='S')
self.assertEqual(len(idx1), periods)
idx2 = pd.date_range(end='2000', periods=periods, freq='S')
self.assertEqual(len(idx2), periods)
def test_intersection(self):
first = self.index
second = self.index[5:]
intersect = first.intersection(second)
self.assertTrue(tm.equalContents(intersect, second))
# GH 10149
cases = [klass(second.values) for klass in [np.array, Series, list]]
for case in cases:
result = first.intersection(case)
self.assertTrue(tm.equalContents(result, second))
third = Index(['a', 'b', 'c'])
result = first.intersection(third)
expected = pd.Index([], dtype=object)
self.assert_index_equal(result, expected)
def test_union(self):
first = self.index[:5]
second = self.index[5:]
everything = self.index
union = first.union(second)
self.assertTrue(tm.equalContents(union, everything))
# GH 10149
cases = [klass(second.values) for klass in [np.array, Series, list]]
for case in cases:
result = first.union(case)
self.assertTrue(tm.equalContents(result, everything))
def test_nat(self):
self.assertIs(DatetimeIndex([np.nan])[0], pd.NaT)
def test_ufunc_coercions(self):
idx = date_range('2011-01-01', periods=3, freq='2D', name='x')
delta = np.timedelta64(1, 'D')
for result in [idx + delta, np.add(idx, delta)]:
tm.assertIsInstance(result, DatetimeIndex)
exp = date_range('2011-01-02', periods=3, freq='2D', name='x')
tm.assert_index_equal(result, exp)
self.assertEqual(result.freq, '2D')
for result in [idx - delta, np.subtract(idx, delta)]:
tm.assertIsInstance(result, DatetimeIndex)
exp = date_range('2010-12-31', periods=3, freq='2D', name='x')
tm.assert_index_equal(result, exp)
self.assertEqual(result.freq, '2D')
delta = np.array([np.timedelta64(1, 'D'), np.timedelta64(2, 'D'),
np.timedelta64(3, 'D')])
for result in [idx + delta, np.add(idx, delta)]:
tm.assertIsInstance(result, DatetimeIndex)
exp = DatetimeIndex(['2011-01-02', '2011-01-05', '2011-01-08'],
freq='3D', name='x')
tm.assert_index_equal(result, exp)
self.assertEqual(result.freq, '3D')
for result in [idx - delta, np.subtract(idx, delta)]:
tm.assertIsInstance(result, DatetimeIndex)
exp = DatetimeIndex(['2010-12-31', '2011-01-01', '2011-01-02'],
freq='D', name='x')
tm.assert_index_equal(result, exp)
self.assertEqual(result.freq, 'D')
def test_fillna_datetime64(self):
# GH 11343
for tz in ['US/Eastern', 'Asia/Tokyo']:
idx = pd.DatetimeIndex(['2011-01-01 09:00', pd.NaT,
'2011-01-01 11:00'])
exp = pd.DatetimeIndex(['2011-01-01 09:00', '2011-01-01 10:00',
'2011-01-01 11:00'])
self.assert_index_equal(
idx.fillna(pd.Timestamp('2011-01-01 10:00')), exp)
# tz mismatch
exp = pd.Index([pd.Timestamp('2011-01-01 09:00'),
pd.Timestamp('2011-01-01 10:00', tz=tz),
pd.Timestamp('2011-01-01 11:00')], dtype=object)
self.assert_index_equal(
idx.fillna(pd.Timestamp('2011-01-01 10:00', tz=tz)), exp)
# object
exp = pd.Index([pd.Timestamp('2011-01-01 09:00'), 'x',
pd.Timestamp('2011-01-01 11:00')], dtype=object)
self.assert_index_equal(idx.fillna('x'), exp)
idx = pd.DatetimeIndex(
['2011-01-01 09:00', pd.NaT, '2011-01-01 11:00'], tz=tz)
exp = pd.DatetimeIndex(
['2011-01-01 09:00', '2011-01-01 10:00', '2011-01-01 11:00'
], tz=tz)
self.assert_index_equal(
idx.fillna(pd.Timestamp('2011-01-01 10:00', tz=tz)), exp)
exp = pd.Index([pd.Timestamp('2011-01-01 09:00', tz=tz),
pd.Timestamp('2011-01-01 10:00'),
pd.Timestamp('2011-01-01 11:00', tz=tz)],
dtype=object)
self.assert_index_equal(
idx.fillna(pd.Timestamp('2011-01-01 10:00')), exp)
# object
exp = pd.Index([pd.Timestamp('2011-01-01 09:00', tz=tz),
'x',
pd.Timestamp('2011-01-01 11:00', tz=tz)],
dtype=object)
self.assert_index_equal(idx.fillna('x'), exp)
def test_contains(self):
#GH13572
dates = ['2015-01-03', '2015-01-01', '2015-01-04', '2015-01-05', '2015-01-02']
monotonic = pd.to_datetime(sorted(dates))
non_monotonic = pd.to_datetime(['2015-01-03', '2015-01-01', '2015-01-04', '2015-01-05', '2015-01-02'])
for idx in [non_monotonic, monotonic]:
self.assertNotIn('2015-01-06', idx)
self.assertNotIn(pd.Timestamp('2015-01-06'), idx)
for dt in reversed(dates):
self.assertIn(dt, idx)
self.assertIn(pd.Timestamp(dt), idx)
class TestPeriodIndex(DatetimeLike, tm.TestCase):
_holder = PeriodIndex
_multiprocess_can_split_ = True
def setUp(self):
self.indices = dict(index=tm.makePeriodIndex(10))
self.setup_indices()
def create_index(self):
return period_range('20130101', periods=5, freq='D')
def test_astype(self):
# GH 13149, GH 13209
idx = PeriodIndex(['2016-05-16', 'NaT', NaT, np.NaN], freq='D')
result = idx.astype(object)
expected = Index([Period('2016-05-16', freq='D')] +
[Period(NaT, freq='D')] * 3, dtype='object')
# Hack because of lack of support for Period null checking (GH12759)
tm.assert_index_equal(result[:1], expected[:1])
result_arr = np.asarray([p.ordinal for p in result], dtype=np.int64)
expected_arr = np.asarray([p.ordinal for p in expected],
dtype=np.int64)
tm.assert_numpy_array_equal(result_arr, expected_arr)
# TODO: When GH12759 is resolved, change the above hack to:
# tm.assert_index_equal(result, expected) # now, it raises.
result = idx.astype(int)
expected = Int64Index([16937] + [-9223372036854775808] * 3,
dtype=np.int64)
tm.assert_index_equal(result, expected)
idx = period_range('1990', '2009', freq='A')
result = idx.astype('i8')
self.assert_index_equal(result, Index(idx.asi8))
self.assert_numpy_array_equal(result.values, idx.values)
def test_astype_raises(self):
# GH 13149, GH 13209
idx = PeriodIndex(['2016-05-16', 'NaT', NaT, np.NaN], freq='D')
self.assertRaises(ValueError, idx.astype, str)
self.assertRaises(ValueError, idx.astype, float)
self.assertRaises(ValueError, idx.astype, 'timedelta64')
self.assertRaises(ValueError, idx.astype, 'timedelta64[ns]')
self.assertRaises(ValueError, idx.astype, 'datetime64')
self.assertRaises(ValueError, idx.astype, 'datetime64[ns]')
def test_shift(self):
# test shift for PeriodIndex
# GH8083
drange = self.create_index()
result = drange.shift(1)
expected = PeriodIndex(['2013-01-02', '2013-01-03', '2013-01-04',
'2013-01-05', '2013-01-06'], freq='D')
self.assert_index_equal(result, expected)
def test_pickle_compat_construction(self):
pass
def test_get_loc(self):
idx = pd.period_range('2000-01-01', periods=3)
for method in [None, 'pad', 'backfill', 'nearest']:
self.assertEqual(idx.get_loc(idx[1], method), 1)
self.assertEqual(
idx.get_loc(idx[1].asfreq('H', how='start'), method), 1)
self.assertEqual(idx.get_loc(idx[1].to_timestamp(), method), 1)
self.assertEqual(
idx.get_loc(idx[1].to_timestamp().to_pydatetime(), method), 1)
self.assertEqual(idx.get_loc(str(idx[1]), method), 1)
idx = pd.period_range('2000-01-01', periods=5)[::2]
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance='1 day'), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=pd.Timedelta('1D')), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=np.timedelta64(1, 'D')), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=timedelta(1)), 1)
with tm.assertRaisesRegexp(ValueError, 'must be convertible'):
idx.get_loc('2000-01-10', method='nearest', tolerance='foo')
msg = 'Input has different freq from PeriodIndex\\(freq=D\\)'
with tm.assertRaisesRegexp(ValueError, msg):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 hour')
with tm.assertRaises(KeyError):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 day')
def test_where(self):
i = self.create_index()
result = i.where(notnull(i))
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = pd.PeriodIndex([pd.NaT, pd.NaT] + i[2:].tolist(),
freq='D')
result = i.where(notnull(i2))
expected = i2
tm.assert_index_equal(result, expected)
def test_where_other(self):
i = self.create_index()
for arr in [np.nan, pd.NaT]:
result = i.where(notnull(i), other=np.nan)
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = pd.PeriodIndex([pd.NaT, pd.NaT] + i[2:].tolist(),
freq='D')
result = i.where(notnull(i2), i2)
tm.assert_index_equal(result, i2)
i2 = i.copy()
i2 = pd.PeriodIndex([pd.NaT, pd.NaT] + i[2:].tolist(),
freq='D')
result = i.where(notnull(i2), i2.values)
tm.assert_index_equal(result, i2)
def test_get_indexer(self):
idx = pd.period_range('2000-01-01', periods=3).asfreq('H', how='start')
tm.assert_numpy_array_equal(idx.get_indexer(idx),
np.array([0, 1, 2], dtype=np.int_))
target = pd.PeriodIndex(['1999-12-31T23', '2000-01-01T12',
'2000-01-02T01'], freq='H')
tm.assert_numpy_array_equal(idx.get_indexer(target, 'pad'),
np.array([-1, 0, 1], dtype=np.int_))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'backfill'),
np.array([0, 1, 2], dtype=np.int_))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest'),
np.array([0, 1, 1], dtype=np.int_))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest',
tolerance='1 hour'),
np.array([0, -1, 1], dtype=np.int_))
msg = 'Input has different freq from PeriodIndex\\(freq=H\\)'
with self.assertRaisesRegexp(ValueError, msg):
idx.get_indexer(target, 'nearest', tolerance='1 minute')
tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest',
tolerance='1 day'),
np.array([0, 1, 1], dtype=np.int_))
def test_repeat(self):
# GH10183
idx = pd.period_range('2000-01-01', periods=3, freq='D')
res = idx.repeat(3)
exp = PeriodIndex(idx.values.repeat(3), freq='D')
self.assert_index_equal(res, exp)
self.assertEqual(res.freqstr, 'D')
def test_period_index_indexer(self):
# GH4125
idx = pd.period_range('2002-01', '2003-12', freq='M')
df = pd.DataFrame(pd.np.random.randn(24, 10), index=idx)
self.assert_frame_equal(df, df.ix[idx])
self.assert_frame_equal(df, df.ix[list(idx)])
self.assert_frame_equal(df, df.loc[list(idx)])
self.assert_frame_equal(df.iloc[0:5], df.loc[idx[0:5]])
self.assert_frame_equal(df, df.loc[list(idx)])
def test_fillna_period(self):
# GH 11343
idx = pd.PeriodIndex(
['2011-01-01 09:00', pd.NaT, '2011-01-01 11:00'], freq='H')
exp = pd.PeriodIndex(
['2011-01-01 09:00', '2011-01-01 10:00', '2011-01-01 11:00'
], freq='H')
self.assert_index_equal(
idx.fillna(pd.Period('2011-01-01 10:00', freq='H')), exp)
exp = pd.Index([pd.Period('2011-01-01 09:00', freq='H'), 'x',
pd.Period('2011-01-01 11:00', freq='H')], dtype=object)
self.assert_index_equal(idx.fillna('x'), exp)
with tm.assertRaisesRegexp(
ValueError,
'Input has different freq=D from PeriodIndex\\(freq=H\\)'):
idx.fillna(pd.Period('2011-01-01', freq='D'))
def test_no_millisecond_field(self):
with self.assertRaises(AttributeError):
DatetimeIndex.millisecond
with self.assertRaises(AttributeError):
DatetimeIndex([]).millisecond
class TestTimedeltaIndex(DatetimeLike, tm.TestCase):
_holder = TimedeltaIndex
_multiprocess_can_split_ = True
def setUp(self):
self.indices = dict(index=tm.makeTimedeltaIndex(10))
self.setup_indices()
def create_index(self):
return pd.to_timedelta(range(5), unit='d') + pd.offsets.Hour(1)
def test_shift(self):
# test shift for TimedeltaIndex
# err8083
drange = self.create_index()
result = drange.shift(1)
expected = TimedeltaIndex(['1 days 01:00:00', '2 days 01:00:00',
'3 days 01:00:00',
'4 days 01:00:00', '5 days 01:00:00'],
freq='D')
self.assert_index_equal(result, expected)
result = drange.shift(3, freq='2D 1s')
expected = TimedeltaIndex(['6 days 01:00:03', '7 days 01:00:03',
'8 days 01:00:03', '9 days 01:00:03',
'10 days 01:00:03'], freq='D')
self.assert_index_equal(result, expected)
def test_astype(self):
# GH 13149, GH 13209
idx = TimedeltaIndex([1e14, 'NaT', pd.NaT, np.NaN])
result = idx.astype(object)
expected = Index([Timedelta('1 days 03:46:40')] + [pd.NaT] * 3,
dtype=object)
tm.assert_index_equal(result, expected)
result = idx.astype(int)
expected = Int64Index([100000000000000] + [-9223372036854775808] * 3,
dtype=np.int64)
tm.assert_index_equal(result, expected)
rng = timedelta_range('1 days', periods=10)
result = rng.astype('i8')
self.assert_index_equal(result, Index(rng.asi8))
self.assert_numpy_array_equal(rng.asi8, result.values)
def test_astype_timedelta64(self):
# GH 13149, GH 13209
idx = TimedeltaIndex([1e14, 'NaT', pd.NaT, np.NaN])
result = idx.astype('timedelta64')
expected = Float64Index([1e+14] + [np.NaN] * 3, dtype='float64')
tm.assert_index_equal(result, expected)
result = idx.astype('timedelta64[ns]')
tm.assert_index_equal(result, idx)
self.assertFalse(result is idx)
result = idx.astype('timedelta64[ns]', copy=False)
tm.assert_index_equal(result, idx)
self.assertTrue(result is idx)
def test_astype_raises(self):
# GH 13149, GH 13209
idx = TimedeltaIndex([1e14, 'NaT', pd.NaT, np.NaN])