pandas.Index.view#

Index.view(cls=None)[source]#

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:

clsdata-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)