numpy.issubdtype(arg1, arg2)
Returns True if first argument is a typecode lower/equal in type hierarchy.
This is like the builtin
, but for
s.
Parameters:arg1, arg2dtype_like
or object coercible to one
Returns:outboolSee also
Overview of the numpy type hierarchy.
Examples
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)TrueSimilar types of different sizes are not subdtypes of each other:
>>> np.issubdtype(np.float64,np.float32)False>>> np.issubdtype(np.float32,np.float64)Falsebut both are subtypes of
:
>>> np.issubdtype(np.float64,np.floating)True>>> np.issubdtype(np.float32,np.floating)TrueFor convenience, dtype-like objects are allowed too:
>>> np.issubdtype('S1',np.bytes_)True>>> np.issubdtype('i4',np.signedinteger)True