Python pandas.tseries.offsets.CDay() Examples
The following are 15
code examples of pandas.tseries.offsets.CDay().
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Example #1
| Source File: test_indexing.py From recruit with Apache License 2.0 | 6 votes |
|
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)]
Example #2
| Source File: test_ops.py From recruit with Apache License 2.0 | 6 votes |
|
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()
Example #3
| Source File: test_indexing.py From vnpy_crypto with MIT License | 6 votes |
|
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)]
Example #4
| Source File: test_ops.py From vnpy_crypto with MIT License | 6 votes |
|
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()
Example #5
| Source File: test_indexing.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
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)]
Example #6
| Source File: test_ops.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
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()
Example #7
| Source File: test_ops.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
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)]
Example #8
| Source File: test_ops.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
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()
Example #9
| Source File: test_indexing.py From coffeegrindsize with MIT License | 6 votes |
|
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)]
Example #10
| Source File: test_ops.py From coffeegrindsize with MIT License | 6 votes |
|
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()
Example #11
| Source File: test_indexing.py From twitter-stock-recommendation with MIT License | 6 votes |
|
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)]
Example #12
| Source File: test_ops.py From twitter-stock-recommendation with MIT License | 6 votes |
|
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()
Example #13
| Source File: datetimes.py From recruit with Apache License 2.0 | 4 votes |
|
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)
Example #14
| Source File: index.py From Computable with MIT License | 4 votes |
|
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)
Example #15
| Source File: datetimes.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
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)
