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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def view(self, dtype=None):
 """ 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 -------- 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: 0 254 1 255 2 0 3 1 4 2 dtype: uint8 The views share the same underlying values: 0 -128 1 -1 2 0 3 1 4 2 dtype: int8 """

        return self._constructor(self._values.view(dtype),
                                 index=self.index).__finalize__(self)