如何将二维 numpy 阵列垂直拆分为新的二维 numpy 阵列？

Question

I have this code that essentially splits a two-dimensional numpy array horizontally and makes a new two-dimensional numpy array out of it.

array1 = np.asarray([[1, 2, 3]])
array2 = np.asarray([[4, 5, 6]])
array3 = np.asarray([[7, 8, 9]])

concatenated = np.concatenate((array1, array2, array3), axis=0)

print(concatenated)

column_split = np.hsplit(concatenated, array1.size)

td_array = []

for array in column_split:
    td_array.append(array.flatten())

print(np.asarray(td_array))

Output of my code: output of the code example

How can I do this with less lines of code? I assume it could be very resource intensive, as soon as I apply this example to my larger task.

Answer 1

I suppose using numpy.hsplit in this case is not necessary and what I am trying to do is covered by the numpy.transpose function.

concatenated = np.concatenate((array1, array2, array3), axis=0)
td_array = concatenated.T

Thank you j1-lee for pointing this out.