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test_scalar_compat.py
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test_scalar_compat.py
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# -*- coding: utf-8 -*-
"""
Tests for DatetimeIndex methods behaving like their Timestamp counterparts
"""
from datetime import datetime
import numpy as np
import pytest
from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
import pandas as pd
from pandas import DatetimeIndex, Timestamp, date_range
import pandas.util.testing as tm
from pandas.tseries.frequencies import to_offset
class TestDatetimeIndexOps(object):
def test_dti_time(self):
rng = date_range('1/1/2000', freq='12min', periods=10)
result = pd.Index(rng).time
expected = [t.time() for t in rng]
assert (result == expected).all()
def test_dti_date(self):
rng = date_range('1/1/2000', freq='12H', periods=10)
result = pd.Index(rng).date
expected = [t.date() for t in rng]
assert (result == expected).all()
@pytest.mark.parametrize('data', [
['1400-01-01'],
[datetime(1400, 1, 1)]])
def test_dti_date_out_of_range(self, data):
# GH#1475
msg = "Out of bounds nanosecond timestamp: 1400-01-01 00:00:00"
with pytest.raises(OutOfBoundsDatetime, match=msg):
DatetimeIndex(data)
@pytest.mark.parametrize('field', [
'dayofweek', 'dayofyear', 'week', 'weekofyear', 'quarter',
'days_in_month', 'is_month_start', 'is_month_end',
'is_quarter_start', 'is_quarter_end', 'is_year_start',
'is_year_end', 'weekday_name'])
def test_dti_timestamp_fields(self, field):
# extra fields from DatetimeIndex like quarter and week
idx = tm.makeDateIndex(100)
expected = getattr(idx, field)[-1]
if field == 'weekday_name':
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
result = getattr(Timestamp(idx[-1]), field)
else:
result = getattr(Timestamp(idx[-1]), field)
assert result == expected
def test_dti_timestamp_freq_fields(self):
# extra fields from DatetimeIndex like quarter and week
idx = tm.makeDateIndex(100)
assert idx.freq == Timestamp(idx[-1], idx.freq).freq
assert idx.freqstr == Timestamp(idx[-1], idx.freq).freqstr
# ----------------------------------------------------------------
# DatetimeIndex.round
def test_round_daily(self):
dti = date_range('20130101 09:10:11', periods=5)
result = dti.round('D')
expected = date_range('20130101', periods=5)
tm.assert_index_equal(result, expected)
dti = dti.tz_localize('UTC').tz_convert('US/Eastern')
result = dti.round('D')
expected = date_range('20130101',
periods=5).tz_localize('US/Eastern')
tm.assert_index_equal(result, expected)
result = dti.round('s')
tm.assert_index_equal(result, dti)
@pytest.mark.parametrize('freq, error_msg', [
('Y', '<YearEnd: month=12> is a non-fixed frequency'),
('M', '<MonthEnd> is a non-fixed frequency'),
('foobar', 'Invalid frequency: foobar')])
def test_round_invalid(self, freq, error_msg):
dti = date_range('20130101 09:10:11', periods=5)
dti = dti.tz_localize('UTC').tz_convert('US/Eastern')
with pytest.raises(ValueError, match=error_msg):
dti.round(freq)
def test_round(self, tz_naive_fixture):
tz = tz_naive_fixture
rng = date_range(start='2016-01-01', periods=5,
freq='30Min', tz=tz)
elt = rng[1]
expected_rng = DatetimeIndex([
Timestamp('2016-01-01 00:00:00', tz=tz, freq='30T'),
Timestamp('2016-01-01 00:00:00', tz=tz, freq='30T'),
Timestamp('2016-01-01 01:00:00', tz=tz, freq='30T'),
Timestamp('2016-01-01 02:00:00', tz=tz, freq='30T'),
Timestamp('2016-01-01 02:00:00', tz=tz, freq='30T'),
])
expected_elt = expected_rng[1]
tm.assert_index_equal(rng.round(freq='H'), expected_rng)
assert elt.round(freq='H') == expected_elt
msg = pd._libs.tslibs.frequencies.INVALID_FREQ_ERR_MSG
with pytest.raises(ValueError, match=msg):
rng.round(freq='foo')
with pytest.raises(ValueError, match=msg):
elt.round(freq='foo')
msg = "<MonthEnd> is a non-fixed frequency"
with pytest.raises(ValueError, match=msg):
rng.round(freq='M')
with pytest.raises(ValueError, match=msg):
elt.round(freq='M')
# GH#14440 & GH#15578
index = DatetimeIndex(['2016-10-17 12:00:00.0015'], tz=tz)
result = index.round('ms')
expected = DatetimeIndex(['2016-10-17 12:00:00.002000'], tz=tz)
tm.assert_index_equal(result, expected)
for freq in ['us', 'ns']:
tm.assert_index_equal(index, index.round(freq))
index = DatetimeIndex(['2016-10-17 12:00:00.00149'], tz=tz)
result = index.round('ms')
expected = DatetimeIndex(['2016-10-17 12:00:00.001000'], tz=tz)
tm.assert_index_equal(result, expected)
index = DatetimeIndex(['2016-10-17 12:00:00.001501031'])
result = index.round('10ns')
expected = DatetimeIndex(['2016-10-17 12:00:00.001501030'])
tm.assert_index_equal(result, expected)
with tm.assert_produces_warning(False):
ts = '2016-10-17 12:00:00.001501031'
DatetimeIndex([ts]).round('1010ns')
def test_no_rounding_occurs(self, tz_naive_fixture):
# GH 21262
tz = tz_naive_fixture
rng = date_range(start='2016-01-01', periods=5,
freq='2Min', tz=tz)
expected_rng = DatetimeIndex([
Timestamp('2016-01-01 00:00:00', tz=tz, freq='2T'),
Timestamp('2016-01-01 00:02:00', tz=tz, freq='2T'),
Timestamp('2016-01-01 00:04:00', tz=tz, freq='2T'),
Timestamp('2016-01-01 00:06:00', tz=tz, freq='2T'),
Timestamp('2016-01-01 00:08:00', tz=tz, freq='2T'),
])
tm.assert_index_equal(rng.round(freq='2T'), expected_rng)
@pytest.mark.parametrize('test_input, rounder, freq, expected', [
(['2117-01-01 00:00:45'], 'floor', '15s', ['2117-01-01 00:00:45']),
(['2117-01-01 00:00:45'], 'ceil', '15s', ['2117-01-01 00:00:45']),
(['2117-01-01 00:00:45.000000012'], 'floor', '10ns',
['2117-01-01 00:00:45.000000010']),
(['1823-01-01 00:00:01.000000012'], 'ceil', '10ns',
['1823-01-01 00:00:01.000000020']),
(['1823-01-01 00:00:01'], 'floor', '1s', ['1823-01-01 00:00:01']),
(['1823-01-01 00:00:01'], 'ceil', '1s', ['1823-01-01 00:00:01']),
(['2018-01-01 00:15:00'], 'ceil', '15T', ['2018-01-01 00:15:00']),
(['2018-01-01 00:15:00'], 'floor', '15T', ['2018-01-01 00:15:00']),
(['1823-01-01 03:00:00'], 'ceil', '3H', ['1823-01-01 03:00:00']),
(['1823-01-01 03:00:00'], 'floor', '3H', ['1823-01-01 03:00:00']),
(('NaT', '1823-01-01 00:00:01'), 'floor', '1s',
('NaT', '1823-01-01 00:00:01')),
(('NaT', '1823-01-01 00:00:01'), 'ceil', '1s',
('NaT', '1823-01-01 00:00:01'))
])
def test_ceil_floor_edge(self, test_input, rounder, freq, expected):
dt = DatetimeIndex(list(test_input))
func = getattr(dt, rounder)
result = func(freq)
expected = DatetimeIndex(list(expected))
assert expected.equals(result)
@pytest.mark.parametrize('start, index_freq, periods', [
('2018-01-01', '12H', 25),
('2018-01-01 0:0:0.124999', '1ns', 1000),
])
@pytest.mark.parametrize('round_freq', [
'2ns', '3ns', '4ns', '5ns', '6ns', '7ns',
'250ns', '500ns', '750ns',
'1us', '19us', '250us', '500us', '750us',
'1s', '2s', '3s',
'12H', '1D',
])
def test_round_int64(self, start, index_freq, periods, round_freq):
dt = date_range(start=start, freq=index_freq, periods=periods)
unit = to_offset(round_freq).nanos
# test floor
result = dt.floor(round_freq)
diff = dt.asi8 - result.asi8
mod = result.asi8 % unit
assert (mod == 0).all(), "floor not a {} multiple".format(round_freq)
assert (0 <= diff).all() and (diff < unit).all(), "floor error"
# test ceil
result = dt.ceil(round_freq)
diff = result.asi8 - dt.asi8
mod = result.asi8 % unit
assert (mod == 0).all(), "ceil not a {} multiple".format(round_freq)
assert (0 <= diff).all() and (diff < unit).all(), "ceil error"
# test round
result = dt.round(round_freq)
diff = abs(result.asi8 - dt.asi8)
mod = result.asi8 % unit
assert (mod == 0).all(), "round not a {} multiple".format(round_freq)
assert (diff <= unit // 2).all(), "round error"
if unit % 2 == 0:
assert (
result.asi8[diff == unit // 2] % 2 == 0
).all(), "round half to even error"
# ----------------------------------------------------------------
# DatetimeIndex.normalize
def test_normalize(self):
rng = date_range('1/1/2000 9:30', periods=10, freq='D')
result = rng.normalize()
expected = date_range('1/1/2000', periods=10, freq='D')
tm.assert_index_equal(result, expected)
arr_ns = np.array([1380585623454345752,
1380585612343234312]).astype("datetime64[ns]")
rng_ns = DatetimeIndex(arr_ns)
rng_ns_normalized = rng_ns.normalize()
arr_ns = np.array([1380585600000000000,
1380585600000000000]).astype("datetime64[ns]")
expected = DatetimeIndex(arr_ns)
tm.assert_index_equal(rng_ns_normalized, expected)
assert result.is_normalized
assert not rng.is_normalized
def test_normalize_nat(self):
dti = DatetimeIndex([pd.NaT, Timestamp('2018-01-01 01:00:00')])
result = dti.normalize()
expected = DatetimeIndex([pd.NaT, Timestamp('2018-01-01')])
tm.assert_index_equal(result, expected)
class TestDateTimeIndexToJulianDate(object):
def test_1700(self):
dr = date_range(start=Timestamp('1710-10-01'), periods=5, freq='D')
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Float64Index)
tm.assert_index_equal(r1, r2)
def test_2000(self):
dr = date_range(start=Timestamp('2000-02-27'), periods=5, freq='D')
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Float64Index)
tm.assert_index_equal(r1, r2)
def test_hour(self):
dr = date_range(start=Timestamp('2000-02-27'), periods=5, freq='H')
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Float64Index)
tm.assert_index_equal(r1, r2)
def test_minute(self):
dr = date_range(start=Timestamp('2000-02-27'), periods=5, freq='T')
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Float64Index)
tm.assert_index_equal(r1, r2)
def test_second(self):
dr = date_range(start=Timestamp('2000-02-27'), periods=5, freq='S')
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Float64Index)
tm.assert_index_equal(r1, r2)