Numpy array with different data types

Question

We both know that: "Numpy array is multidimensional array of objects of all the same type"

However, I could create a Numpy array that contains different data types as example below. Can anyone give an explain, how it could be.

import numpy as np
a = np.array([('a',1),('b',2)],dtype=[('alpha','U11'),('num','i8')])
print(a[0][1]+1)
print(len(a[0][0]))

Output:

2
1

• hpaulj: print a, and its shape. And index by fild name

Answer 1

Those are numpy records:

• https://numpy.org/doc/stable/user/basics.rec.html

Numpy provides two data structures, the homogeneous arrays and the structured (aka record) arrays. The latter one, what you just stumbled across, is a structure that not only allows you to have different data types (float, int, str, etc.) but also provides handy methods to access them, through labels for instance.

Answer 2

In Numpy: it's called Structured arrays

Please read more here: https://numpy.org/doc/stable/user/basics.rec.html

P/S: thanks Brandt