def repeat(self, repeats, *args, **kwargs):
"""
Analogous to ndarray.repeat
"""
nv.validate_repeat(args, kwargs)
if isinstance(self, ABCPeriodIndex):
freq = self.freq
else:
freq = None
return self._shallow_copy(self.asi8.repeat(repeats), freq=freq)
def repeat(self, repeats, *args, **kwargs):
"""
Analogous to ndarray.repeat.
"""
nv.validate_repeat(args, kwargs)
if is_period_dtype(self):
freq = self.freq
else:
freq = None
return self._shallow_copy(self.asi8.repeat(repeats),
freq=freq)
def repeat(self, n, *args, **kwargs):
"""
Return a new Index of the values repeated `n` times.
See also
--------
numpy.ndarray.repeat
"""
nv.validate_repeat(args, kwargs)
# overwrites method from DatetimeIndexOpsMixin
return self._shallow_copy(self.values.repeat(n))
def repeat(self, repeats, *args, **kwargs):
"""
Repeat elements of a PeriodArray.
See also
--------
numpy.ndarray.repeat
"""
# TODO(DatetimeArray): remove
nv.validate_repeat(args, kwargs)
values = self._data.repeat(repeats)
return type(self)(values, self.freq)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
ind = np.arange(len(self)).repeat(repeats)
return self.take(ind)
def repeat(self, repeats, axis=None):
nv.validate_repeat((), {"axis": axis})
ind = np.arange(len(self)).repeat(repeats)
return self.take(ind)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
result = type(self._data)(self.asi8.repeat(repeats), dtype=self.dtype)
return self._shallow_copy(result)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
freq = self.freq if is_period_dtype(self) else None
return self._shallow_copy(self.asi8.repeat(repeats), freq=freq)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
left_repeat = self.left.repeat(repeats)
right_repeat = self.right.repeat(repeats)
return self._shallow_copy(left=left_repeat, right=right_repeat)
def repeat(self, repeats, axis=None):
nv.validate_repeat((), {"axis": axis})
result = self._data.repeat(repeats, axis=axis)
return type(self)._simple_new(result, name=self.name)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
ind = np.arange(len(self)).repeat(repeats)
return self.take(ind)
def repeat(self, repeats, *args, **kwargs):
"""
Analogous to ndarray.repeat
"""
nv.validate_repeat(args, kwargs)
return self._shallow_copy(self.values.repeat(repeats), freq=None)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
combined = self._combined.repeat(repeats, 0)
return type(self)._simple_new(combined, closed=self.closed)
def repeat(self, repeats, axis=None):
nv.validate_repeat((), {"axis": axis})
left_repeat = self.left.repeat(repeats)
right_repeat = self.right.repeat(repeats)
return self._shallow_copy(left=left_repeat, right=right_repeat)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
result = self._data.repeat(repeats, axis=axis)
return type(self)._simple_new(result, name=self.name)
def repeat(self, repeats, *args, **kwargs):
"""
Analogous to ndarray.repeat
"""
nv.validate_repeat(args, kwargs)
return self._shallow_copy(self.values.repeat(repeats), freq=None)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
left_repeat = self.left.repeat(repeats)
right_repeat = self.right.repeat(repeats)
return self._shallow_copy(left=left_repeat, right=right_repeat)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
freq = self.freq if is_period_dtype(self) else None
return self._shallow_copy(self.asi8.repeat(repeats), freq=freq)
def repeat(self, repeats, axis=None):
nv.validate_repeat(tuple(), dict(axis=axis))
result = self._data.repeat(repeats, axis=axis)
return self._shallow_copy(result)
def repeat(self, repeats, *args, **kwargs):
nv.validate_repeat(args, kwargs)
freq = self.freq if is_period_dtype(self) else None
return self._shallow_copy(self.asi8.repeat(repeats), freq=freq)
