Python pandas.tseries.offsets.Day() Examples

The following are 30 code examples of pandas.tseries.offsets.Day(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.tseries.offsets , or try the search function .
Example #1
Source File: common_holidays.py    From trading_calendars with Apache License 2.0 6 votes vote down vote up 
def chinese_national_day(start_date=None, end_date=None, observance=None):
    return Holiday(
        "Chinese National Day",
        month=10,
        day=1,
        start_date=start_date,
        end_date=end_date,
        observance=observance,
    )


# Precomputed Chinese Lunar Year dates.
#
# See Also
# --------
# trading_calendars/etc/lunisolar chinese-new-year
Example #2
Source File: test_offsets.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #3
Source File: test_offsets.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = BDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #4
Source File: test_offsets.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CBMonthEnd()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 8, 31)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 28)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #5
Source File: test_period_index.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_with_local_timezone_pytz(self):
        # see gh-5430
        local_timezone = pytz.timezone('America/Los_Angeles')

        start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
                         tzinfo=pytz.utc)
        # 1 day later
        end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
                       tzinfo=pytz.utc)

        index = pd.date_range(start, end, freq='H')

        series = Series(1, index=index)
        series = series.tz_convert(local_timezone)
        result = series.resample('D', kind='period').mean()

        # Create the expected series
        # Index is moved back a day with the timezone conversion from UTC to
        # Pacific
        expected_index = (pd.period_range(start=start, end=end, freq='D') -
                          offsets.Day())
        expected = Series(1, index=expected_index)
        assert_series_equal(result, expected)
Example #6
Source File: test_period_index.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_with_local_timezone_dateutil(self):
        # see gh-5430
        local_timezone = 'dateutil/America/Los_Angeles'

        start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
                         tzinfo=dateutil.tz.tzutc())
        # 1 day later
        end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
                       tzinfo=dateutil.tz.tzutc())

        index = pd.date_range(start, end, freq='H', name='idx')

        series = Series(1, index=index)
        series = series.tz_convert(local_timezone)
        result = series.resample('D', kind='period').mean()

        # Create the expected series
        # Index is moved back a day with the timezone conversion from UTC to
        # Pacific
        expected_index = (pd.period_range(start=start, end=end, freq='D',
                                          name='idx') - offsets.Day())
        expected = Series(1, index=expected_index)
        assert_series_equal(result, expected)
Example #7
Source File: test_pickle.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def compare_series_ts(result, expected, typ, version):
    # GH 7748
    tm.assert_series_equal(result, expected)
    assert result.index.freq == expected.index.freq
    assert not result.index.freq.normalize
    tm.assert_series_equal(result > 0, expected > 0)

    # GH 9291
    freq = result.index.freq
    assert freq + Day(1) == Day(2)

    res = freq + pd.Timedelta(hours=1)
    assert isinstance(res, pd.Timedelta)
    assert res == pd.Timedelta(days=1, hours=1)

    res = freq + pd.Timedelta(nanoseconds=1)
    assert isinstance(res, pd.Timedelta)
    assert res == pd.Timedelta(days=1, nanoseconds=1)
Example #8
Source File: test_pickle.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def compare_series_ts(result, expected, typ, version):
    # GH 7748
    tm.assert_series_equal(result, expected)
    assert result.index.freq == expected.index.freq
    assert not result.index.freq.normalize
    tm.assert_series_equal(result > 0, expected > 0)

    # GH 9291
    freq = result.index.freq
    assert freq + Day(1) == Day(2)

    res = freq + pd.Timedelta(hours=1)
    assert isinstance(res, pd.Timedelta)
    assert res == pd.Timedelta(days=1, hours=1)

    res = freq + pd.Timedelta(nanoseconds=1)
    assert isinstance(res, pd.Timedelta)
    assert res == pd.Timedelta(days=1, nanoseconds=1)
Example #9
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CBMonthEnd()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 8, 31)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 28)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #10
Source File: test_period_index.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_with_local_timezone_dateutil(self):
        # see gh-5430
        local_timezone = 'dateutil/America/Los_Angeles'

        start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
                         tzinfo=dateutil.tz.tzutc())
        # 1 day later
        end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
                       tzinfo=dateutil.tz.tzutc())

        index = pd.date_range(start, end, freq='H', name='idx')

        series = Series(1, index=index)
        series = series.tz_convert(local_timezone)
        result = series.resample('D', kind='period').mean()

        # Create the expected series
        # Index is moved back a day with the timezone conversion from UTC to
        # Pacific
        expected_index = (pd.period_range(start=start, end=end, freq='D',
                                          name='idx') - offsets.Day())
        expected = Series(1, index=expected_index)
        assert_series_equal(result, expected)
Example #11
Source File: test_period_index.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_with_local_timezone_pytz(self):
        # see gh-5430
        local_timezone = pytz.timezone('America/Los_Angeles')

        start = datetime(year=2013, month=11, day=1, hour=0, minute=0,
                         tzinfo=pytz.utc)
        # 1 day later
        end = datetime(year=2013, month=11, day=2, hour=0, minute=0,
                       tzinfo=pytz.utc)

        index = pd.date_range(start, end, freq='H')

        series = Series(1, index=index)
        series = series.tz_convert(local_timezone)
        result = series.resample('D', kind='period').mean()

        # Create the expected series
        # Index is moved back a day with the timezone conversion from UTC to
        # Pacific
        expected_index = (pd.period_range(start=start, end=end, freq='D') -
                          offsets.Day())
        expected = Series(1, index=expected_index)
        assert_series_equal(result, expected)
Example #12
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #13
Source File: common_holidays.py    From trading_calendars with Apache License 2.0 6 votes vote down vote up 
def european_labour_day(start_date=None,
                        end_date=None,
                        observance=None,
                        days_of_week=None):
    return Holiday(
        "Labour Day",
        month=5,
        day=1,
        start_date=start_date,
        end_date=end_date,
        observance=observance,
        days_of_week=days_of_week,
    )


# Holy Wednesday, Maundy Thursday, Ascension Day, Whit Monday, and Corpus
# Christi do not take observance as a parameter because they depend on a
# particular offset, and offset and observance cannot both be passed to a
# Holiday.
Example #14
Source File: test_pickle.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def compare_series_ts(result, expected, typ, version):
    # GH 7748
    tm.assert_series_equal(result, expected)
    assert result.index.freq == expected.index.freq
    assert not result.index.freq.normalize
    tm.assert_series_equal(result > 0, expected > 0)

    # GH 9291
    freq = result.index.freq
    assert freq + Day(1) == Day(2)

    res = freq + pandas.Timedelta(hours=1)
    assert isinstance(res, pandas.Timedelta)
    assert res == pandas.Timedelta(days=1, hours=1)

    res = freq + pandas.Timedelta(nanoseconds=1)
    assert isinstance(res, pandas.Timedelta)
    assert res == pandas.Timedelta(days=1, nanoseconds=1)
Example #15
Source File: test_offsets.py    From Computable with MIT License 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        self.assertEqual(result, datetime(2012, 9, 14))

        result = offset.rollforward(dt)
        self.assertEqual(result, datetime(2012, 9, 17))

        offset = offsets.Day()
        result = offset.rollback(dt)
        self.assertEqual(result, datetime(2012, 9, 15))

        result = offset.rollforward(dt)
        self.assertEqual(result, datetime(2012, 9, 15))
Example #16
Source File: test_offsets.py    From Computable with MIT License 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = BDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        self.assertEqual(result, datetime(2012, 9, 14))

        result = offset.rollforward(dt)
        self.assertEqual(result, datetime(2012, 9, 17))

        offset = offsets.Day()
        result = offset.rollback(dt)
        self.assertEqual(result, datetime(2012, 9, 15))

        result = offset.rollforward(dt)
        self.assertEqual(result, datetime(2012, 9, 15))
Example #17
Source File: test_offsets.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = BDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #18
Source File: test_offsets.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #19
Source File: test_offsets.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = CBMonthEnd()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 8, 31)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 28)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #20
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_roll_date_object(self):
        offset = BDay()

        dt = date(2012, 9, 15)

        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 14)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 17)

        offset = offsets.Day()
        result = offset.rollback(dt)
        assert result == datetime(2012, 9, 15)

        result = offset.rollforward(dt)
        assert result == datetime(2012, 9, 15)
Example #21
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_corner(self):
        with pytest.raises(ValueError):
            Week(weekday=7)

        with pytest.raises(ValueError, match="Day must be"):
            Week(weekday=-1)
Example #22
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_constructor(self):
        with pytest.raises(ValueError, match="^Week"):
            WeekOfMonth(n=1, week=4, weekday=0)

        with pytest.raises(ValueError, match="^Week"):
            WeekOfMonth(n=1, week=-1, weekday=0)

        with pytest.raises(ValueError, match="^Day"):
            WeekOfMonth(n=1, week=0, weekday=-1)

        with pytest.raises(ValueError, match="^Day"):
            WeekOfMonth(n=1, week=0, weekday=-7)
Example #23
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_pickle_v0_15_2(self, datapath):
        offsets = {'DateOffset': DateOffset(years=1),
                   'MonthBegin': MonthBegin(1),
                   'Day': Day(1),
                   'YearBegin': YearBegin(1),
                   'Week': Week(1)}

        pickle_path = datapath('tseries', 'offsets', 'data',
                               'dateoffset_0_15_2.pickle')
        # This code was executed once on v0.15.2 to generate the pickle:
        # with open(pickle_path, 'wb') as f: pickle.dump(offsets, f)
        #
        tm.assert_dict_equal(offsets, read_pickle(pickle_path))
Example #24
Source File: test_offsets.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_constructor(self):
        with pytest.raises(ValueError, match="^N cannot be 0"):
            LastWeekOfMonth(n=0, weekday=1)

        with pytest.raises(ValueError, match="^Day"):
            LastWeekOfMonth(n=1, weekday=-1)

        with pytest.raises(ValueError, match="^Day"):
            LastWeekOfMonth(n=1, weekday=7)
Example #25
Source File: test_ticks.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_delta_to_tick():
    delta = timedelta(3)

    tick = offsets._delta_to_tick(delta)
    assert (tick == offsets.Day(3))

    td = Timedelta(nanoseconds=5)
    tick = offsets._delta_to_tick(td)
    assert tick == Nano(5)
Example #26
Source File: test_qcut.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_qcut_nat(ser):
    # see gh-19768
    intervals = IntervalIndex.from_tuples([
        (ser[0] - Nano(), ser[2] - Day()),
        np.nan, (ser[2] - Day(), ser[2])])
    expected = Series(Categorical(intervals, ordered=True))

    result = qcut(ser, 2)
    tm.assert_series_equal(result, expected)
Example #27
Source File: test_interval_range.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_constructor_coverage(self):
        # float value for periods
        expected = interval_range(start=0, periods=10)
        result = interval_range(start=0, periods=10.5)
        tm.assert_index_equal(result, expected)

        # equivalent timestamp-like start/end
        start, end = Timestamp('2017-01-01'), Timestamp('2017-01-15')
        expected = interval_range(start=start, end=end)

        result = interval_range(start=start.to_pydatetime(),
                                end=end.to_pydatetime())
        tm.assert_index_equal(result, expected)

        result = interval_range(start=start.asm8, end=end.asm8)
        tm.assert_index_equal(result, expected)

        # equivalent freq with timestamp
        equiv_freq = ['D', Day(), Timedelta(days=1), timedelta(days=1),
                      DateOffset(days=1)]
        for freq in equiv_freq:
            result = interval_range(start=start, end=end, freq=freq)
            tm.assert_index_equal(result, expected)

        # equivalent timedelta-like start/end
        start, end = Timedelta(days=1), Timedelta(days=10)
        expected = interval_range(start=start, end=end)

        result = interval_range(start=start.to_pytimedelta(),
                                end=end.to_pytimedelta())
        tm.assert_index_equal(result, expected)

        result = interval_range(start=start.asm8, end=end.asm8)
        tm.assert_index_equal(result, expected)

        # equivalent freq with timedelta
        equiv_freq = ['D', Day(), Timedelta(days=1), timedelta(days=1)]
        for freq in equiv_freq:
            result = interval_range(start=start, end=end, freq=freq)
            tm.assert_index_equal(result, expected)
Example #28
Source File: exchange_calendar_xpra.py    From trading_calendars with Apache License 2.0 5 votes vote down vote up 
def adhoc_holidays(self):
        return [
            # Extreme Flooding
            pd.Timestamp('2002-08-14', tz=UTC),
            # Restoration of the Czech Independence Day
            pd.Timestamp('2004-01-02', tz=UTC),
            pd.Timestamp('2005-01-03', tz=UTC),
        ]
Example #29
Source File: test_timedelta_range.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_timedelta_range(self):

        expected = to_timedelta(np.arange(5), unit='D')
        result = timedelta_range('0 days', periods=5, freq='D')
        tm.assert_index_equal(result, expected)

        expected = to_timedelta(np.arange(11), unit='D')
        result = timedelta_range('0 days', '10 days', freq='D')
        tm.assert_index_equal(result, expected)

        expected = to_timedelta(np.arange(5), unit='D') + Second(2) + Day()
        result = timedelta_range('1 days, 00:00:02', '5 days, 00:00:02',
                                 freq='D')
        tm.assert_index_equal(result, expected)

        expected = to_timedelta([1, 3, 5, 7, 9], unit='D') + Second(2)
        result = timedelta_range('1 days, 00:00:02', periods=5, freq='2D')
        tm.assert_index_equal(result, expected)

        expected = to_timedelta(np.arange(50), unit='T') * 30
        result = timedelta_range('0 days', freq='30T', periods=50)
        tm.assert_index_equal(result, expected)

        # GH 11776
        arr = np.arange(10).reshape(2, 5)
        df = pd.DataFrame(np.arange(10).reshape(2, 5))
        for arg in (arr, df):
            with pytest.raises(TypeError, match="1-d array"):
                to_timedelta(arg)
            for errors in ['ignore', 'raise', 'coerce']:
                with pytest.raises(TypeError, match="1-d array"):
                    to_timedelta(arg, errors=errors)

        # issue10583
        df = pd.DataFrame(np.random.normal(size=(10, 4)))
        df.index = pd.timedelta_range(start='0s', periods=10, freq='s')
        expected = df.loc[pd.Timedelta('0s'):, :]
        result = df.loc['0s':, :]
        tm.assert_frame_equal(expected, result)
Example #30
Source File: common_holidays.py    From trading_calendars with Apache License 2.0 5 votes vote down vote up 
def whit_monday(start_date=None, end_date=None):
    return Holiday(
        "Whit Monday",
        month=1,
        day=1,
        offset=[Easter(), Day(50)],
        start_date=start_date,
        end_date=end_date,
    )