Scalar Objects VS dtype

Just a clarification:

When I store an object from a narray with dtype (for example) float64, this means the stored variable is of scalar object of float64's .type attribute.

>>> somearray = numpy.array([1,2,3,4,5], dtype='float64')
>>> somefloat = somearray[0]
>>> type(somefloat)
<type 'numpy.float64'>



So numpy.float64 is a scalar type. The dtype is only there to tell the numpy array how to handle the data in the array.