def _maybe_convert_timedelta(self, other):
if isinstance(other,
(timedelta, np.timedelta64, offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq.rule_code)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return nanos // offset_nanos
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq.rule_code:
return other.n
elif isinstance(other, np.ndarray):
if com.is_integer_dtype(other):
return other
elif com.is_timedelta64_dtype(other):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if (nanos % offset_nanos).all() == 0:
return nanos // offset_nanos
msg = "Input has different freq from PeriodIndex(freq={0})"
raise ValueError(msg.format(self.freqstr))
def __new__(cls, data=None, ordinal=None,
freq=None, start=None, end=None, periods=None,
copy=False, name=None,
year=None, month=None, quarter=None, day=None,
hour=None, minute=None, second=None):
freq = _freq_mod.get_standard_freq(freq)
if periods is not None:
if com.is_float(periods):
periods = int(periods)
elif not com.is_integer(periods):
raise ValueError('Periods must be a number, got %s' %
str(periods))
if data is None:
if ordinal is not None:
data = np.asarray(ordinal, dtype=np.int64)
else:
fields = [year, month, quarter, day, hour, minute, second]
data, freq = cls._generate_range(start, end, periods,
freq, fields)
else:
ordinal, freq = cls._from_arraylike(data, freq)
data = np.array(ordinal, dtype=np.int64, copy=False)
subarr = data.view(cls)
subarr.name = name
subarr.freq = freq
return subarr
def _maybe_convert_timedelta(self, other):
if isinstance(other,
(timedelta, np.timedelta64, offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq.rule_code)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return nanos // offset_nanos
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq.rule_code:
return other.n
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
elif isinstance(other, np.ndarray):
if com.is_integer_dtype(other):
return other
elif com.is_timedelta64_dtype(other):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if (nanos % offset_nanos).all() == 0:
return nanos // offset_nanos
# raise when input doesn't have freq
msg = "Input has different freq from PeriodIndex(freq={0})"
raise IncompatibleFrequency(msg.format(self.freqstr))
def __new__(cls, data=None, ordinal=None, freq=None, start=None, end=None,
periods=None, copy=False, name=None, year=None, month=None,
quarter=None, day=None, hour=None, minute=None, second=None,
tz=None):
freq = _freq_mod.get_standard_freq(freq)
if periods is not None:
if com.is_float(periods):
periods = int(periods)
elif not com.is_integer(periods):
raise ValueError('Periods must be a number, got %s' %
str(periods))
if data is None:
if ordinal is not None:
data = np.asarray(ordinal, dtype=np.int64)
else:
fields = [year, month, quarter, day, hour, minute, second]
data, freq = cls._generate_range(start, end, periods,
freq, fields)
else:
ordinal, freq = cls._from_arraylike(data, freq, tz)
data = np.array(ordinal, dtype=np.int64, copy=False)
subarr = data.view(cls)
subarr.name = name
subarr.freq = freq
return subarr
def __new__(cls,
data=None,
ordinal=None,
freq=None,
start=None,
end=None,
periods=None,
copy=False,
name=None,
tz=None,
**kwargs):
freq = frequencies.get_standard_freq(freq)
if periods is not None:
if is_float(periods):
periods = int(periods)
elif not is_integer(periods):
raise ValueError('Periods must be a number, got %s' %
str(periods))
if data is None:
if ordinal is not None:
data = np.asarray(ordinal, dtype=np.int64)
else:
data, freq = cls._generate_range(start, end, periods, freq,
kwargs)
else:
ordinal, freq = cls._from_arraylike(data, freq, tz)
data = np.array(ordinal, dtype=np.int64, copy=False)
return cls._simple_new(data, name=name, freq=freq)
def test_frequency_misc(self):
assert (resolution.get_freq_group('T') ==
frequencies.FreqGroup.FR_MIN)
code, stride = frequencies.get_freq_code(offsets.Hour())
assert code == frequencies.FreqGroup.FR_HR
code, stride = frequencies.get_freq_code((5, 'T'))
assert code == frequencies.FreqGroup.FR_MIN
assert stride == 5
offset = offsets.Hour()
result = frequencies.to_offset(offset)
assert result == offset
result = frequencies.to_offset((5, 'T'))
expected = offsets.Minute(5)
assert result == expected
with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
frequencies.get_freq_code((5, 'baz'))
with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
frequencies.to_offset('100foo')
with tm.assert_raises_regex(ValueError, 'Could not evaluate'):
frequencies.to_offset(('', ''))
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = frequencies.get_standard_freq(offsets.Hour())
assert result == 'H'
def _maybe_convert_timedelta(self, other):
if isinstance(other, (timedelta, np.timedelta64, offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq.rule_code)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return nanos // offset_nanos
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq.rule_code:
return other.n
elif isinstance(other, np.ndarray):
if com.is_integer_dtype(other):
return other
elif com.is_timedelta64_dtype(other):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if (nanos % offset_nanos).all() == 0:
return nanos // offset_nanos
msg = "Input has different freq from PeriodIndex(freq={0})"
raise ValueError(msg.format(self.freqstr))
def __new__(cls, data=None, ordinal=None,
freq=None, start=None, end=None, periods=None,
copy=False, name=None,
year=None, month=None, quarter=None, day=None,
hour=None, minute=None, second=None):
if isinstance(freq, Period):
freq = freq.freq
else:
freq = _freq_mod.get_standard_freq(freq)
if data is None:
if ordinal is not None:
data = np.asarray(ordinal, dtype=np.int64)
else:
fields = [year, month, quarter, day, hour, minute, second]
data, freq = cls._generate_range(start, end, periods,
freq, fields)
else:
ordinal, freq = cls._from_arraylike(data, freq)
data = np.array(ordinal, dtype=np.int64, copy=False)
subarr = data.view(cls)
subarr.name = name
subarr.freq = freq
return subarr
def asfreq(self, freq=None, how='E'):
how = _validate_end_alias(how)
freq = _freq_mod.get_standard_freq(freq)
base1, mult1 = _gfc(self.freq)
if isinstance(freq, basestring):
base2, mult2 = _gfc(freq)
else:
base2, mult2 = freq
if mult2 != 1:
raise ValueError('Only mult == 1 supported')
if how not in ('S', 'E'):
raise ValueError('relation argument must be one of S or E')
end = how == 'E'
new_data = lib.period_asfreq_arr(self.values, base1, base2, end)
result = new_data.view(PeriodIndex)
result.name = self.name
result.freq = freq
return result
def test_frequency_misc(self):
assert (resolution.get_freq_group('T') == frequencies.FreqGroup.FR_MIN)
code, stride = frequencies.get_freq_code(offsets.Hour())
assert code == frequencies.FreqGroup.FR_HR
code, stride = frequencies.get_freq_code((5, 'T'))
assert code == frequencies.FreqGroup.FR_MIN
assert stride == 5
offset = offsets.Hour()
result = frequencies.to_offset(offset)
assert result == offset
result = frequencies.to_offset((5, 'T'))
expected = offsets.Minute(5)
assert result == expected
with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
frequencies.get_freq_code((5, 'baz'))
with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
frequencies.to_offset('100foo')
with tm.assert_raises_regex(ValueError, 'Could not evaluate'):
frequencies.to_offset(('', ''))
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = frequencies.get_standard_freq(offsets.Hour())
assert result == 'H'
def asfreq(self, freq=None, how='E'):
how = _validate_end_alias(how)
freq = _freq_mod.get_standard_freq(freq)
base1, mult1 = _gfc(self.freq)
if isinstance(freq, basestring):
base2, mult2 = _gfc(freq)
else:
base2, mult2 = freq
if mult2 != 1:
raise ValueError('Only mult == 1 supported')
if how not in ('S', 'E'):
raise ValueError('relation argument must be one of S or E')
end = how == 'E'
new_data = plib.period_asfreq_arr(self.values, base1, base2, end)
result = new_data.view(PeriodIndex)
result.name = self.name
result.freq = freq
return result
def __new__(
cls,
data=None,
ordinal=None,
freq=None,
start=None,
end=None,
periods=None,
copy=False,
name=None,
tz=None,
**kwargs
):
freq = frequencies.get_standard_freq(freq)
if periods is not None:
if com.is_float(periods):
periods = int(periods)
elif not com.is_integer(periods):
raise ValueError("Periods must be a number, got %s" % str(periods))
if data is None:
if ordinal is not None:
data = np.asarray(ordinal, dtype=np.int64)
else:
data, freq = cls._generate_range(start, end, periods, freq, kwargs)
else:
ordinal, freq = cls._from_arraylike(data, freq, tz)
data = np.array(ordinal, dtype=np.int64, copy=False)
return cls._simple_new(data, name=name, freq=freq)
def _maybe_convert_timedelta(self, other):
if isinstance(other, (timedelta, np.timedelta64,
offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq.rule_code)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return nanos // offset_nanos
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq.rule_code:
return other.n
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
elif isinstance(other, np.ndarray):
if com.is_integer_dtype(other):
return other
elif com.is_timedelta64_dtype(other):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if (nanos % offset_nanos).all() == 0:
return nanos // offset_nanos
# raise when input doesn't have freq
msg = "Input has different freq from PeriodIndex(freq={0})"
raise IncompatibleFrequency(msg.format(self.freqstr))
def test_frequency_misc(self):
self.assertEquals(fmod.get_freq_group('T'),
fmod.FreqGroup.FR_MIN)
code, stride = fmod.get_freq_code(offsets.Hour())
self.assertEquals(code, fmod.FreqGroup.FR_HR)
code, stride = fmod.get_freq_code((5, 'T'))
self.assertEquals(code, fmod.FreqGroup.FR_MIN)
self.assertEquals(stride, 5)
offset = offsets.Hour()
result = fmod.to_offset(offset)
self.assertEquals(result, offset)
result = fmod.to_offset((5, 'T'))
expected = offsets.Minute(5)
self.assertEquals(result, expected)
self.assertRaises(KeyError, fmod.get_freq_code, (5, 'baz'))
self.assertRaises(ValueError, fmod.to_offset, '100foo')
self.assertRaises(ValueError, fmod.to_offset, ('', ''))
result = fmod.get_standard_freq(offsets.Hour())
self.assertEquals(result, 'H')
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 = _freq_mod.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 = tslib.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)
def _add_delta(self, other):
if isinstance(other, (timedelta, np.timedelta64, offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return self.shift(nanos // offset_nanos)
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq:
return self.shift(other.n)
raise ValueError("Input has different freq from PeriodIndex(freq={0})".format(self.freq))
def _add_delta(self, other):
if isinstance(other, (timedelta, np.timedelta64, offsets.Tick, Timedelta)):
offset = frequencies.to_offset(self.freq)
if isinstance(offset, offsets.Tick):
nanos = tslib._delta_to_nanoseconds(other)
offset_nanos = tslib._delta_to_nanoseconds(offset)
if nanos % offset_nanos == 0:
return self.shift(nanos // offset_nanos)
elif isinstance(other, offsets.DateOffset):
freqstr = frequencies.get_standard_freq(other)
base = frequencies.get_base_alias(freqstr)
if base == self.freq:
return self.shift(other.n)
raise ValueError("Input has different freq from PeriodIndex(freq={0})".format(self.freq))
def asfreq(self, freq=None, how='E'):
how = _validate_end_alias(how)
freq = _freq_mod.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 = plib.period_asfreq_arr(self.values, base1, base2, end)
result = new_data.view(PeriodIndex)
result.name = self.name
result.freq = freq
return result
def asfreq(self, freq=None, how='E'):
how = _validate_end_alias(how)
freq = _freq_mod.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 = plib.period_asfreq_arr(self.values, base1, base2, end)
result = new_data.view(PeriodIndex)
result.name = self.name
result.freq = freq
return result
def __new__(cls, data=None,
freq=None, start=None, end=None, periods=None,
copy=False, name=None):
if isinstance(freq, Period):
freq = freq.freq
else:
freq = _freq_mod.get_standard_freq(freq)
if data is None:
subarr, freq = _get_ordinal_range(start, end, periods, freq)
subarr = subarr.view(cls)
subarr.name = name
subarr.freq = freq
return subarr
if not isinstance(data, np.ndarray):
if np.isscalar(data):
raise ValueError('PeriodIndex() must be called with a '
'collection of some kind, %s was passed'
% repr(data))
elif isinstance(data, Period):
raise ValueError('Data must be array of dates, strings, '
'or Period objects')
# other iterable of some kind
if not isinstance(data, (list, tuple)):
data = list(data)
try:
data = np.array(data, dtype='i8')
except:
data = np.array(data, dtype='O')
if freq is None and len(data) > 0:
freq = getattr(data[0], 'freq', None)
if freq is None:
raise ValueError(('freq not specified and cannot be inferred '
'from first element'))
data = _period_unbox_array(data, check=freq)
else:
if isinstance(data, PeriodIndex):
if freq is None or freq == data.freq:
freq = data.freq
data = data.values
else:
base1, mult1 = _gfc(data.freq)
base2, mult2 = _gfc(freq)
how = py3compat.str_to_bytes('E')
data = lib.period_asfreq_arr(data.values, base1, mult1,
base2, mult2, how)
else:
if freq is None and len(data) > 0:
freq = getattr(data[0], 'freq')
if freq is None:
raise ValueError(('freq not specified and cannot be '
'inferred from first element'))
if data.dtype == np.datetime64:
data = dt64arr_to_periodarr(data, freq)
elif data.dtype == np.int64:
pass
else:
try:
data = data.astype('i8')
except:
data = data.astype('O')
data = _period_unbox_array(data, check=freq)
data = np.array(data, dtype=np.int64, copy=False)
if (data <= 0).any():
raise ValueError("Found illegal (<= 0) values in data")
subarr = data.view(cls)
subarr.name = name
subarr.freq = freq
return subarr
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)
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:
mask = asi8 == tslib.iNaT
new_data[mask] = 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)
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:
mask = asi8 == tslib.iNaT
new_data[mask] = tslib.iNaT
return self._simple_new(new_data, self.name, freq=freq)