def astype(self, dtype, copy=True):
dtype = np.dtype(dtype)
if is_object_dtype(dtype):
return self.asobject
elif is_integer_dtype(dtype):
return Index(self.values.astype('i8', copy=copy),
name=self.name,
dtype='i8')
raise ValueError('Cannot cast PeriodIndex to dtype %s' % dtype)
def _sub_period(self, other):
if self.freq != other.freq:
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
asi8 = self.asi8
new_data = asi8 - other.ordinal
if self.hasnans:
new_data = new_data.astype(np.float64)
new_data[self._isnan] = np.nan
# result must be Int64Index or Float64Index
return Index(new_data, name=self.name)
def astype(self, dtype, copy=True, how='start'):
dtype = pandas_dtype(dtype)
if is_object_dtype(dtype):
return self.asobject
elif is_integer_dtype(dtype):
return Index(self.values.astype('i8', copy=copy), name=self.name,
dtype='i8')
elif is_datetime64_dtype(dtype):
return self.to_timestamp(how=how)
elif is_datetime64tz_dtype(dtype):
return self.to_timestamp(how=how).tz_localize(dtype.tz)
elif is_period_dtype(dtype):
return self.asfreq(freq=dtype.freq)
raise ValueError('Cannot cast PeriodIndex to dtype %s' % dtype)
def _sub_period(self, other):
if self.freq != other.freq:
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
if other.ordinal == tslib.iNaT:
new_data = np.empty(len(self))
new_data.fill(np.nan)
else:
asi8 = self.asi8
new_data = asi8 - other.ordinal
if self.hasnans:
mask = asi8 == tslib.iNaT
new_data = new_data.astype(np.float64)
new_data[mask] = np.nan
# result must be Int64Index or Float64Index
return Index(new_data, name=self.name)
def append(self, other):
"""
Append a collection of Index options together
Parameters
----------
other : Index or list/tuple of indices
Returns
-------
appended : Index
"""
name = self.name
to_concat = [self]
if isinstance(other, (list, tuple)):
to_concat = to_concat + list(other)
else:
to_concat.append(other)
for obj in to_concat:
if isinstance(obj, Index) and obj.name != name:
name = None
break
to_concat = self._ensure_compat_concat(to_concat)
if isinstance(to_concat[0], PeriodIndex):
if len(set([x.freq for x in to_concat])) > 1:
# box
to_concat = [x.asobject.values for x in to_concat]
else:
cat_values = np.concatenate([x.values for x in to_concat])
return PeriodIndex(cat_values, freq=self.freq, name=name)
to_concat = [
x.values if isinstance(x, Index) else x for x in to_concat
]
return Index(com._concat_compat(to_concat), name=name)
def asobject(self):
from pandas.core.index import Index
return Index(self._box_values(self.values), dtype=object)
def asobject(self):
return Index(self._box_values(self.values), dtype=object)
def f(self):
base, mult = _gfc(self.freq)
result = get_period_field_arr(alias, self._values, base)
return Index(result, name=self.name)
