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# pandas.Index.view

Index.view(cls=None)

  Return a view of the Index with the specified dtype or a new Index instance.

  This method returns a view of the calling Index object if no arguments are provided. If a dtype is specified through the cls argument, it attempts to return a view of the Index with the specified dtype. Note that viewing the Index as a different dtype reinterprets the underlying data, which can lead to unexpected results for non-numeric or incompatible dtype conversions.

  Parameters:
    cls data-type or ndarray sub-class, optional

      Data-type descriptor of the returned view, e.g., float32 or int16. Omitting it results in the view having the same data-type as self. This argument can also be specified as an ndarray sub-class, e.g., np.int64 or np.float32 which then specifies the type of the returned object.

  Returns:
    Index or ndarray

      A view of the Index. If cls is None, the returned object is an Index view with the same dtype as the calling object. If a numeric cls is specified an ndarray view with the new dtype is returned.

  Raises:
    ValueError

      If attempting to change to a dtype in a way that is not compatible with the original dtype’s memory layout, for example, viewing an ‘int64’ Index as ‘str’.

  See also

  `Index.copy`

    Returns a copy of the Index.

  `numpy.ndarray.view`

    Returns a new view of array with the same data.

  Examples

      >>> idx = pd.Index([-1, 0, 1])
      >>> idx.view()
      Index([-1, 0, 1], dtype='int64')

      >>> idx.view(np.uint64)
      array([18446744073709551615,                    0,                    1],
        dtype=uint64)

  Viewing as ‘int32’ or ‘float32’ reinterprets the memory, which may lead to unexpected behavior:

      >>> idx.view("float32")
      array([   nan,    nan, 0.e+00, 0.e+00, 1.e-45, 0.e+00], dtype=float32)