def asfreq(self, freq=None, how='E'):
"""
Convert the PeriodIndex to the specified frequency `freq`.
Parameters
----------
freq : str
a frequency
how : str {'E', 'S'}
'E', 'END', or 'FINISH' for end,
'S', 'START', or 'BEGIN' for start.
Whether the elements should be aligned to the end
or start within pa period. January 31st ('END') vs.
Janury 1st ('START') for example.
Returns
-------
new : PeriodIndex with the new frequency
Examples
--------
>>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
>>> pidx
<class 'pandas.tseries.period.PeriodIndex'>
[2010, ..., 2015]
Length: 6, Freq: A-DEC
>>> pidx.asfreq('M')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-12, ..., 2015-12]
Length: 6, Freq: M
>>> pidx.asfreq('M', how='S')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-01, ..., 2015-01]
Length: 6, Freq: M
"""
how = _validate_end_alias(how)
freq = Period._maybe_convert_freq(freq)
base1, mult1 = _gfc(self.freq)
base2, mult2 = _gfc(freq)
asi8 = self.asi8
# mult1 can't be negative or 0
end = how == 'E'
if end:
ordinal = asi8 + mult1 - 1
else:
ordinal = asi8
new_data = period.period_asfreq_arr(ordinal, base1, base2, end)
if self.hasnans:
new_data[self._isnan] = tslib.iNaT
return self._simple_new(new_data, self.name, freq=freq)
def to_timestamp(self, freq=None, how='start'):
"""
Cast to DatetimeIndex
Parameters
----------
freq : string or DateOffset, default 'D' for week or longer, 'S'
otherwise
Target frequency
how : {'s', 'e', 'start', 'end'}
Returns
-------
DatetimeIndex
"""
how = _validate_end_alias(how)
if freq is None:
base, mult = _gfc(self.freq)
freq = frequencies.get_to_timestamp_base(base)
else:
freq = Period._maybe_convert_freq(freq)
base, mult = _gfc(freq)
new_data = self.asfreq(freq, how)
new_data = period.periodarr_to_dt64arr(new_data._values, base)
return DatetimeIndex(new_data, freq='infer', name=self.name)
def to_timestamp(self, freq=None, how='start'):
"""
Cast to DatetimeIndex
Parameters
----------
freq : string or DateOffset, default 'D' for week or longer, 'S'
otherwise
Target frequency
how : {'s', 'e', 'start', 'end'}
Returns
-------
DatetimeIndex
"""
how = _validate_end_alias(how)
if freq is None:
base, mult = _gfc(self.freq)
freq = frequencies.get_to_timestamp_base(base)
else:
freq = Period._maybe_convert_freq(freq)
base, mult = _gfc(freq)
new_data = self.asfreq(freq, how)
new_data = period.periodarr_to_dt64arr(new_data.values, base)
return DatetimeIndex(new_data, freq='infer', name=self.name)
def asfreq(self, freq=None, how='E'):
"""
Convert the PeriodIndex to the specified frequency `freq`.
Parameters
----------
freq : str
a frequency
how : str {'E', 'S'}
'E', 'END', or 'FINISH' for end,
'S', 'START', or 'BEGIN' for start.
Whether the elements should be aligned to the end
or start within pa period. January 31st ('END') vs.
Janury 1st ('START') for example.
Returns
-------
new : PeriodIndex with the new frequency
Examples
--------
>>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
>>> pidx
<class 'pandas.tseries.period.PeriodIndex'>
[2010, ..., 2015]
Length: 6, Freq: A-DEC
>>> pidx.asfreq('M')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-12, ..., 2015-12]
Length: 6, Freq: M
>>> pidx.asfreq('M', how='S')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-01, ..., 2015-01]
Length: 6, Freq: M
"""
how = _validate_end_alias(how)
freq = Period._maybe_convert_freq(freq)
base1, mult1 = _gfc(self.freq)
base2, mult2 = _gfc(freq)
asi8 = self.asi8
# mult1 can't be negative or 0
end = how == 'E'
if end:
ordinal = asi8 + mult1 - 1
else:
ordinal = asi8
new_data = period.period_asfreq_arr(ordinal, base1, base2, end)
if self.hasnans:
new_data[self._isnan] = tslib.iNaT
return self._simple_new(new_data, self.name, freq=freq)
def asfreq(self, freq=None, how='E'):
"""
Convert the PeriodIndex to the specified frequency `freq`.
Parameters
----------
freq : str
a frequency
how : str {'E', 'S'}
'E', 'END', or 'FINISH' for end,
'S', 'START', or 'BEGIN' for start.
Whether the elements should be aligned to the end
or start within pa period. January 31st ('END') vs.
Janury 1st ('START') for example.
Returns
-------
new : PeriodIndex with the new frequency
Examples
--------
>>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
>>> pidx
<class 'pandas.tseries.period.PeriodIndex'>
[2010, ..., 2015]
Length: 6, Freq: A-DEC
>>> pidx.asfreq('M')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-12, ..., 2015-12]
Length: 6, Freq: M
>>> pidx.asfreq('M', how='S')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-01, ..., 2015-01]
Length: 6, Freq: M
"""
how = _validate_end_alias(how)
freq = frequencies.get_standard_freq(freq)
base1, mult1 = _gfc(self.freq)
base2, mult2 = _gfc(freq)
if mult2 != 1:
raise ValueError('Only mult == 1 supported')
end = how == 'E'
new_data = period.period_asfreq_arr(self.values, base1, base2, end)
return self._simple_new(new_data, self.name, freq=freq)
def asfreq(self, freq=None, how='E'):
"""
Convert the PeriodIndex to the specified frequency `freq`.
Parameters
----------
freq : str
a frequency
how : str {'E', 'S'}
'E', 'END', or 'FINISH' for end,
'S', 'START', or 'BEGIN' for start.
Whether the elements should be aligned to the end
or start within pa period. January 31st ('END') vs.
Janury 1st ('START') for example.
Returns
-------
new : PeriodIndex with the new frequency
Examples
--------
>>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
>>> pidx
<class 'pandas.tseries.period.PeriodIndex'>
[2010, ..., 2015]
Length: 6, Freq: A-DEC
>>> pidx.asfreq('M')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-12, ..., 2015-12]
Length: 6, Freq: M
>>> pidx.asfreq('M', how='S')
<class 'pandas.tseries.period.PeriodIndex'>
[2010-01, ..., 2015-01]
Length: 6, Freq: M
"""
how = _validate_end_alias(how)
freq = frequencies.get_standard_freq(freq)
base1, mult1 = _gfc(self.freq)
base2, mult2 = _gfc(freq)
if mult2 != 1:
raise ValueError('Only mult == 1 supported')
end = how == 'E'
new_data = period.period_asfreq_arr(self.values, base1, base2, end)
return self._simple_new(new_data, self.name, freq=freq)
def asfreq(self, freq=None, how='E'):
how = _validate_end_alias(how)
freq = frequencies.get_standard_freq(freq)
base1, mult1 = _gfc(self.freq)
base2, mult2 = _gfc(freq)
if mult2 != 1:
raise ValueError('Only mult == 1 supported')
end = how == 'E'
new_data = period.period_asfreq_arr(self.values, base1, base2, end)
return self._simple_new(new_data, self.name, freq=freq)