Any solution for merging 2D array into a list?

I’m working on a linear regression with python for my school project. And I want to merge my 7*12 2D-array into 1D list.
Here’s my original array.

y = df["fatalProb"].values.reshape(7,12)
print(y)

[[0.3725 0.4336 0.537  0.392  0.233  0.2892 0.2721 0.2392 0.2281 0.2689
  0.2898 0.2825]
 [0.3112 0.3936 0.3874 0.2793 0.2416 0.275  0.2802 0.2587 0.2583 0.258
  0.2906 0.2927]
 [0.3486 0.3278 0.3836 0.3041 0.2477 0.2734 0.276  0.2903 0.2531 0.2659
  0.2928 0.2896]
 [0.3044 0.4032 0.3665 0.3275 0.2939 0.2882 0.3089 0.2949 0.2547 0.2699
  0.2973 0.2869]
 [0.3488 0.3651 0.4307 0.3361 0.2833 0.3035 0.3051 0.2898 0.2695 0.271
  0.2787 0.3034]
 [0.3559 0.3357 0.4075 0.3428 0.2834 0.3156 0.2952 0.2992 0.2795 0.2806
  0.2905 0.267 ]
 [0.3965 0.3814 0.4735 0.3813 0.3089 0.3105 0.3282 0.3047 0.2834 0.2974
  0.2737 0.2986]]

I wanted my y to be 12-length list.
It’s a list with all the values added that has a same index in each lists. (sorry for the bad English)

e.g.)

[[a,b,c],[d,e,f],[g,h,i]] to [a+d+g,b+e+h,c+f+i]

I thought about using list comprehension. But I was not so happy to use

y = [y[0][j]+y[1][j]+y[2][j]+y[3][j]+y[4][j]+y[5][j]+y[6][j] for j in range(len(y[0]))]

>Solution :

you can use :

l=[]
k=[]
for j in range(len(y[0])):
    for i in range(0,7):
        l.append(y[i][j])
    k.append(sum(l))
y=k

out :

print(y)
    [2.4379,
     5.0783000000000005,
     8.0645,
     10.4276,
     12.319400000000002,
     14.3748,
     16.4405,
     18.417299999999997,
     20.243899999999996,
     22.155599999999993,
     24.168999999999997,
     26.189699999999995]

check len y :

len(y)
12