numpy.issubdtype#
- numpy.issubdtype(arg1, arg2)[source]#
Returns True if first argument is a typecode lower/equal in type hierarchy.
This is like the builtin
issubclass
, but fordtype
s.- Parameters
- arg1, arg2dtype_like
dtype
or object coercible to one
- Returns
- outbool
See also
- Scalars
Overview of the numpy type hierarchy.
issubsctype
,issubclass_
Examples
issubdtype
can be used to check the type of arrays:>>> ints = np.array([1, 2, 3], dtype=np.int32) >>> np.issubdtype(ints.dtype, np.integer) True >>> np.issubdtype(ints.dtype, np.floating) False
>>> floats = np.array([1, 2, 3], dtype=np.float32) >>> np.issubdtype(floats.dtype, np.integer) False >>> np.issubdtype(floats.dtype, np.floating) True
Similar types of different sizes are not subdtypes of each other:
>>> np.issubdtype(np.float64, np.float32) False >>> np.issubdtype(np.float32, np.float64) False
but both are subtypes of
floating
:>>> np.issubdtype(np.float64, np.floating) True >>> np.issubdtype(np.float32, np.floating) True
For convenience, dtype-like objects are allowed too:
>>> np.issubdtype('S1', np.string_) True >>> np.issubdtype('i4', np.signedinteger) True