Manipulating values of a 2D array in python using a loop (using numpy)

Question

import random as rand 

weights = np.zeros((3, 4))

print(weights, end = "\n\n")

for i in weights:
  for j in i:
    j = rand.randint(1, 10)

print(weights)

So I was playing around with numpy and decided to make a 2D array filled with 0s. I then wanted to change the values of the elements within the array to random numbers between 1 and 10. Using the above code, the 2D array does not change and remains filled with zeros. Why does python behave this way when it comes to arrays?

To get my desired result, I had to do the following:

import numpy as np
import random as rand 

weights = np.zeros((3, 4))

print(weights, end = "\n\n")

for i in range(len(weights)):
  for j in range(len(weights[i])):
    weights[i][j] = rand.randint(1, 9)

print(weights)

Is there any better way to do this so that I don't have to resort to using range() and len()?

np.random.rand(3, 4)

Parth Shah
– Parth Shah

2020-07-11 06:47:07 +00:00
Commented Jul 11, 2020 at 6:47 — Parth Shah
– Parth Shah, Commented Jul 11, 2020 at 6:47
Or for random ints - np.random.randint(1, 9, (3, 4))

Parth Shah
– Parth Shah

2020-07-11 06:49:45 +00:00
Commented Jul 11, 2020 at 6:49 — Parth Shah
– Parth Shah, Commented Jul 11, 2020 at 6:49

Parth Shah · Accepted Answer · 2020-07-11 07:01:47Z

1

Better way to do it is during init:

# args - low, high, shape
weights = np.random.randint(1, 9, (3, 4))

You can read documentation here.

And as to why python behaves this way, with list comprehension you are not modifying the list, you are creating a new list.

edited Jul 11, 2020 at 7:01

answered Jul 11, 2020 at 6:51

Parth Shah

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