Looping through each item in a numpy array?

Question

I\'m trying to access each item in a numpy 2D array.

I\'m used to something like this in Python [[...], [...], [...]]

for row in data:
    for col in dat         


        

Answer 1

Try np.ndenumerate:

>>> a =numpy.array([[1,2],[3,4]])
>>> for (i,j), value in np.ndenumerate(a):
...  print(i, j, value)
... 
0 0 1
0 1 2 
1 0 3
1 1 4

Answer 2

If you want to access an item in a numpy 2D array features, you can use features[row_index, column_index]. If you wanted to iterate through a numpy array, you could just modify your script to

for row in data:

    for col in data:

       print(data[row, col])

Answer 3

Make a small 2d array, and a nested list from it:

In [241]: A=np.arange(6).reshape(2,3)
In [242]: alist= A.tolist()
In [243]: alist
Out[243]: [[0, 1, 2], [3, 4, 5]]

One way of iterating on the list:

In [244]: for row in alist:
     ...:     for item in row:
     ...:         print(item)
     ...:         
0
1
2
3
4
5

works just same for the array

In [245]: for row in A:
     ...:     for item in row:
     ...:         print(item)
     ...:         
0
1
2
3
4
5

Now neither is good if you want to modify elements. But for crude iteration over all elements this works.

WIth the array I can easily treat it was a 1d

In [246]: [i for i in A.flat]
Out[246]: [0, 1, 2, 3, 4, 5]

I could also iterate with nested indices

In [247]: [A[i,j] for i in range(A.shape[0]) for j in range(A.shape[1])]
Out[247]: [0, 1, 2, 3, 4, 5]

In general it is better to work with arrays without iteration. I give these iteration examples to clearup some confusion.