Python offsets.CDay方法代码示例

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def test_dti_custom_getitem(self):
        rng = pd.bdate_range(START, END, freq='C')
        smaller = rng[:5]
        exp = DatetimeIndex(rng.view(np.ndarray)[:5])
        tm.assert_index_equal(smaller, exp)
        assert smaller.freq == rng.freq

        sliced = rng[::5]
        assert sliced.freq == CDay() * 5

        fancy_indexed = rng[[4, 3, 2, 1, 0]]
        assert len(fancy_indexed) == 5
        assert isinstance(fancy_indexed, DatetimeIndex)
        assert fancy_indexed.freq is None

        # 32-bit vs. 64-bit platforms
        assert rng[4] == rng[np.int_(4)] 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def test_shift(self):

        shifted = self.rng.shift(5)
        assert shifted[0] == self.rng[5]
        assert shifted.freq == self.rng.freq

        shifted = self.rng.shift(-5)
        assert shifted[5] == self.rng[0]
        assert shifted.freq == self.rng.freq

        shifted = self.rng.shift(0)
        assert shifted[0] == self.rng[0]
        assert shifted.freq == self.rng.freq

        with warnings.catch_warnings(record=True):
            warnings.simplefilter("ignore", pd.errors.PerformanceWarning)
            rng = date_range(START, END, freq=BMonthEnd())
            shifted = rng.shift(1, freq=CDay())
            assert shifted[0] == rng[0] + CDay() 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def test_shift(self):

        shifted = self.rng.shift(5)
        assert shifted[0] == self.rng[5]
        assert shifted.freq == self.rng.freq

        shifted = self.rng.shift(-5)
        assert shifted[5] == self.rng[0]
        assert shifted.freq == self.rng.freq

        shifted = self.rng.shift(0)
        assert shifted[0] == self.rng[0]
        assert shifted.freq == self.rng.freq

        # PerformanceWarning
        with warnings.catch_warnings(record=True):
            rng = date_range(START, END, freq=BMonthEnd())
            shifted = rng.shift(1, freq=CDay())
            assert shifted[0] == rng[0] + CDay() 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def test_getitem(self):
        smaller = self.rng[:5]
        exp = DatetimeIndex(self.rng.view(np.ndarray)[:5])
        tm.assert_index_equal(smaller, exp)
        assert smaller.offset == self.rng.offset

        sliced = self.rng[::5]
        assert sliced.offset == CDay() * 5

        fancy_indexed = self.rng[[4, 3, 2, 1, 0]]
        assert len(fancy_indexed) == 5
        assert isinstance(fancy_indexed, DatetimeIndex)
        assert fancy_indexed.freq is None

        # 32-bit vs. 64-bit platforms
        assert self.rng[4] == self.rng[np.int_(4)] 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def test_shift(self):

        shifted = self.rng.shift(5)
        assert shifted[0] == self.rng[5]
        assert shifted.offset == self.rng.offset

        shifted = self.rng.shift(-5)
        assert shifted[5] == self.rng[0]
        assert shifted.offset == self.rng.offset

        shifted = self.rng.shift(0)
        assert shifted[0] == self.rng[0]
        assert shifted.offset == self.rng.offset

        # PerformanceWarning
        with warnings.catch_warnings(record=True):
            rng = date_range(START, END, freq=BMonthEnd())
            shifted = rng.shift(1, freq=CDay())
            assert shifted[0] == rng[0] + CDay() 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def cdate_range(start=None, end=None, periods=None, freq='C', tz=None,
                normalize=True, name=None, closed=None, **kwargs):
    """
    Return a fixed frequency DatetimeIndex, with CustomBusinessDay as the
    default frequency

    .. deprecated:: 0.21.0

    Parameters
    ----------
    start : string or datetime-like, default None
        Left bound for generating dates
    end : string or datetime-like, default None
        Right bound for generating dates
    periods : integer, default None
        Number of periods to generate
    freq : string or DateOffset, default 'C' (CustomBusinessDay)
        Frequency strings can have multiples, e.g. '5H'
    tz : string, default None
        Time zone name for returning localized DatetimeIndex, for example
        Asia/Beijing
    normalize : bool, default False
        Normalize start/end dates to midnight before generating date range
    name : string, default None
        Name of the resulting DatetimeIndex
    weekmask : string, Default 'Mon Tue Wed Thu Fri'
        weekmask of valid business days, passed to ``numpy.busdaycalendar``
    holidays : list
        list/array of dates to exclude from the set of valid business days,
        passed to ``numpy.busdaycalendar``
    closed : string, default None
        Make the interval closed with respect to the given frequency to
        the 'left', 'right', or both sides (None)

    Notes
    -----
    Of the three parameters: ``start``, ``end``, and ``periods``, exactly two
    must be specified.

    To learn more about the frequency strings, please see `this link
    <http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.

    Returns
    -------
    rng : DatetimeIndex
    """
    warnings.warn("cdate_range is deprecated and will be removed in a future "
                  "version, instead use pd.bdate_range(..., freq='{freq}')"
                  .format(freq=freq), FutureWarning, stacklevel=2)

    if freq == 'C':
        holidays = kwargs.pop('holidays', [])
        weekmask = kwargs.pop('weekmask', 'Mon Tue Wed Thu Fri')
        freq = CDay(holidays=holidays, weekmask=weekmask)

    return date_range(start=start, end=end, periods=periods, freq=freq,
                      tz=tz, normalize=normalize, name=name,
                      closed=closed, **kwargs) 

# 需要导入模块: from pandas.tseries import offsets [as 别名]
# 或者: from pandas.tseries.offsets import CDay [as 别名]
def cdate_range(start=None, end=None, periods=None, freq='C', tz=None,
                normalize=True, name=None, closed=None, **kwargs):
    """
    **EXPERIMENTAL** Return a fixed frequency datetime index, with
    CustomBusinessDay as the default frequency

    .. warning:: EXPERIMENTAL

        The CustomBusinessDay class is not officially supported and the API is
        likely to change in future versions. Use this at your own risk.

    Parameters
    ----------
    start : string or datetime-like, default None
        Left bound for generating dates
    end : string or datetime-like, default None
        Right bound for generating dates
    periods : integer or None, default None
        If None, must specify start and end
    freq : string or DateOffset, default 'C' (CustomBusinessDay)
        Frequency strings can have multiples, e.g. '5H'
    tz : string or None
        Time zone name for returning localized DatetimeIndex, for example
        Asia/Beijing
    normalize : bool, default False
        Normalize start/end dates to midnight before generating date range
    name : str, default None
        Name for the resulting index
    weekmask : str, Default 'Mon Tue Wed Thu Fri'
        weekmask of valid business days, passed to ``numpy.busdaycalendar``
    holidays : list
        list/array of dates to exclude from the set of valid business days,
        passed to ``numpy.busdaycalendar``
    closed : string or None, default None
        Make the interval closed with respect to the given frequency to
        the 'left', 'right', or both sides (None)

    Notes
    -----
    2 of start, end, or periods must be specified

    Returns
    -------
    rng : DatetimeIndex
    """

    if freq=='C':
        holidays = kwargs.pop('holidays', [])
        weekmask = kwargs.pop('weekmask', 'Mon Tue Wed Thu Fri')
        freq = CDay(holidays=holidays, weekmask=weekmask)
    return DatetimeIndex(start=start, end=end, periods=periods, freq=freq,
                         tz=tz, normalize=normalize, name=name,
                         closed=closed, **kwargs)