def view(self, dtype=None):
return self._constructor(self._values.view(dtype),<EOL>index=self.index).__finalize__(self)<EOL>
Create a new view of the Series.

This function will return a new Series with a view of the same
underlying values in memory, optionally reinterpreted with a new data
type. The new data type must preserve the same size in bytes as to not
cause index misalignment.

Parameters
----------
dtype : data type
    Data type object or one of their string representations.

Returns
-------
Series
    A new Series object as a view of the same data in memory.

See Also
--------
numpy.ndarray.view : Equivalent numpy function to create a new view of
    the same data in memory.

Notes
-----
Series are instantiated with ``dtype=float64`` by default. While
``numpy.ndarray.view()`` will return a view with the same data type as
the original array, ``Series.view()`` (without specified dtype)
will try using ``float64`` and may fail if the original data type size
in bytes is not the same.

Examples
--------
>>> s = pd.Series([-2, -1, 0, 1, 2], dtype='int8')
>>> s
0   -2
1   -1
2    0
3    1
4    2
dtype: int8

The 8 bit signed integer representation of `-1` is `0b11111111`, but
the same bytes represent 255 if read as an 8 bit unsigned integer:

>>> us = s.view('uint8')
>>> us
0    254
1    255
2      0
3      1
4      2
dtype: uint8

The views share the same underlying values:

>>> us[0] = 128
>>> s
0   -128
1     -1
2      0
3      1
4      2
dtype: int8