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Method view

pandas/core/indexes/base.py:1033–1109  ·  view source on GitHub ↗

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 s

(self, cls=None)

Source from the content-addressed store, hash-verified

1031 return self[:]
1032
1033 def view(self, cls=None):
1034 """
1035 Return a view of the Index with the specified dtype or a new Index instance.
1036
1037 This method returns a view of the calling Index object if no arguments are
1038 provided. If a dtype is specified through the `cls` argument, it attempts
1039 to return a view of the Index with the specified dtype. Note that viewing
1040 the Index as a different dtype reinterprets the underlying data, which can
1041 lead to unexpected results for non-numeric or incompatible dtype conversions.
1042
1043 Parameters
1044 ----------
1045 cls : data-type or ndarray sub-class, optional
1046 Data-type descriptor of the returned view, e.g., float32 or int16.
1047 Omitting it results in the view having the same data-type as `self`.
1048 This argument can also be specified as an ndarray sub-class,
1049 e.g., np.int64 or np.float32 which then specifies the type of
1050 the returned object.
1051
1052 Returns
1053 -------
1054 Index or ndarray
1055 A view of the Index. If `cls` is None, the returned object is an Index
1056 view with the same dtype as the calling object. If a numeric `cls` is
1057 specified an ndarray view with the new dtype is returned.
1058
1059 Raises
1060 ------
1061 ValueError
1062 If attempting to change to a dtype in a way that is not compatible with
1063 the original dtype's memory layout, for example, viewing an 'int64' Index
1064 as 'str'.
1065
1066 See Also
1067 --------
1068 Index.copy : Returns a copy of the Index.
1069 numpy.ndarray.view : Returns a new view of array with the same data.
1070
1071 Examples
1072 --------
1073 >>> idx = pd.Index([-1, 0, 1])
1074 >>> idx.view()
1075 Index([-1, 0, 1], dtype='int64')
1076
1077 >>> idx.view(np.uint64)
1078 array([18446744073709551615, 0, 1],
1079 dtype=uint64)
1080
1081 Viewing as 'int32' or 'float32' reinterprets the memory, which may lead to
1082 unexpected behavior:
1083
1084 >>> idx.view("float32")
1085 array([ nan, nan, 0.e+00, 0.e+00, 1.e-45, 0.e+00], dtype=float32)
1086 """
1087 # we need to see if we are subclassing an
1088 # index type here
1089 if cls is not None:
1090 dtype = cls

Callers 15

test_is_Method · 0.95
setupMethod · 0.45
setupMethod · 0.45
_get_valuesFunction · 0.45
_wrap_resultsFunction · 0.45
nanstdFunction · 0.45
__array__Method · 0.45
diffMethod · 0.45
_ensure_dataFunction · 0.45
diffFunction · 0.45

Calls 5

_dtype_to_subclassMethod · 0.95
_viewMethod · 0.95
pandas_dtypeFunction · 0.90
needs_i8_conversionFunction · 0.90
_simple_newMethod · 0.45

Tested by 2

test_is_Method · 0.76