I have a 2 numpy arrays in the following format
array([[2, 2, 7, 1],
[5, 0, 3, 1],
[2, 9, 8, 8],
[5, 7, 7, 6]])
and
array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
I want to combine these to the following format
array([[[2, 2, 7, 1],[1,2,3,4]],
[[5, 0, 3, 1],[5,6,7,8]],
[[2, 9, 8, 8],[9,10,11,12]],
[[5, 7, 7, 6],[13,14,15,16]]])
The real data which I am handling contains very large amount of data(5000 in one row). SO working with pandas doesnt solve the case. Is there any efficient method when the data is very huge for creating a format like this
You are looking for stack
arr1 = np.array([[2, 2, 7, 1],
[5, 0, 3, 1],
[2, 9, 8, 8],
[5, 7, 7, 6]])
arr2 = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
arr3 = np.stack((arr1, arr2), axis=1)
print(arr3)
Output
[[[ 2 2 7 1]
[ 1 2 3 4]]
[[ 5 0 3 1]
[ 5 6 7 8]]
[[ 2 9 8 8]
[ 9 10 11 12]]
[[ 5 7 7 6]
[13 14 15 16]]]
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