[Python Cookbook] Numpy: Iterating Over Arrays

1. Using for-loop

Iterate along row axis:

import numpy as np
x=np.array([[1,2,3],[4,5,6]])
for i in x:
    print(x)

Output:

[1 2 3]

[4 5 6]

Iterate by index:

for i in range(len(x)):
    print(x[i])

Output:

[1 2 3]

[4 5 6]

Iterate by row and index:

for i, row in enumerate(x):
    print('row', i, 'is', row)

Output:

row 0 is [1 2 3]

row 1 is [4 5 6]

 

2. Using ndenumerate object

for index, i in np.ndenumerate(x): 
    print(index,i)

Output:

(0, 0) 1

(0, 1) 2

(0, 2) 3

(1, 0) 4

(1, 1) 5

(1, 2) 6

 

3. Using nditer object

See: https://docs.scipy.org/doc/numpy-1.15.0/reference/arrays.nditer.html

 

4. Use zip to iterate over multiple iterables

x2 = x**2
print(x2,'\n')
for i, j in zip(x, x2):
    print(i,'+',j,'=',i+j)

Output:

[[ 1  4  9]

 [16 25 36]] 

 

[1 2 3] + [1 4 9] = [ 2  6 12]

[4 5 6] + [16 25 36] = [20 30 42]