import numpy as np
a1 = [1,2,3,4,5]
a2 = [6,7,8,9,10]
sc = np.empty((0, 2))
#sc = np.append(np.array([a1[0],a2[0]]))
#sc = np.append([a1[1],a2[1]])
sc = np.c_([a1],[a2])
#sc = np.array([a1[1],a2[1]])
print(sc)
print(sc[0])
I have tried to merge the two normal arrays but cannot find a way to do so. The desired result is sc[0] = [1 6] and sc[1] = [2 7], etc.. where [1 6] is treated as a single value.
I can see lots of error on trying different methods, is there any other possible method.
I am not 100% sure what you are trying, but this should do the trick:
import numpy as np
a1 = [1, 2, 3, 4, 5]
a2 = [6, 7, 8, 9, 10]
s = np.c_[a1, a2]
>>> s
array([[ 1, 6],
[ 2, 7],
[ 3, 8],
[ 4, 9],
[ 5, 10]])
>>> s[0]
array([1, 6])
column_stack and avoid the transpose?
You could use zip to feed the array constructor with the values in the right shape:
import numpy as np
a1 = [1,2,3,4,5]
a2 = [6,7,8,9,10]
sc=np.array([*zip(a1,a2)])
print(sc)
[[ 1 6]
[ 2 7]
[ 3 8]
[ 4 9]
[ 5 10]]
Or you could use reshape on the concatenation of the two lists:
sc = np.reshape(a1+a2,(-1,2),order="F")
