Python: converting multi-dimensional numpy arrays into list of arrays

Question

Suppose I have 2D array, for simplicity, a=np.array([[1,2],[3,4]]). I want to convert it to list of arrays, so that the result would be:

b=[np.array([1,2]), np.array([3,4])]

I found out that there is np.ndarray.tolist() function, but it converts N-D array into nested list. I could have done in a for loop (using append method), but it is not efficient/elegant.

In my real example I am working with 2D arrays of approximately 10000 x 50 elements and I want list that contains 50 one dimensional arrays, each of the shape (10000,).

• hpaulj: To iterate on the 2nd dimension, you may want to transpose the array first.

Answer 1

How about using list:

a=np.array([[1,2],[3,4]])
b = list(a)

• Sheldore: Wow. This is the shortest possible solution I guess :)

Answer 2

Why don't you use list comprehension as follows without using any append:

a=np.array([[1,2],[3,4]])
b = [i for i in a]
print (b)

Output

[array([1, 2]), array([3, 4])]

• juanpa.arrivillaga: [i for i in a] is a verbose way of sayin list(a)
• Sheldore: Hmm you are right. But I guess in terms of timings, they shouldn't be different. Under the hood runs the same things IMO
• juanpa.arrivillaga: about the same, but no they do not. list will be faster.
• Sheldore: That's the beauty of SO. You get to know different and more efficient approaches. Thanks for the comment :)
• juanpa.arrivillaga: check out this question for some gory details