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

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

hpaulj
– hpaulj

2021-08-01 09:14:03 +00:00
Commented Aug 1, 2021 at 9:14 — hpaulj
– hpaulj, Commented Aug 1, 2021 at 9:14

Brandt · Accepted Answer · 2021-08-01 08:45:13Z

4

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.

edited Aug 1, 2021 at 8:45

answered Aug 1, 2021 at 8:37

Brandt

5,7293 gold badges35 silver badges50 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

neikel · Accepted Answer · 2021-08-01 08:52:27Z

1

In Numpy: it's called Structured arrays

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

P/S: thanks Brandt

answered Aug 1, 2021 at 8:52

neikel

1051 silver badge9 bronze badges

Collectives™ on Stack Overflow

Numpy array with different data types

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related