Question

What I want to do is take a numpy array like this:

[[1, 2,  4, 7,  9, 15,  0],
 [3, 4,  3, 5, 10,  2, -2],
 [5, 6, 56, 7, 20,  1,  2]]

I want to take each rows last column and divide that by the previous row’s 4th column and take the result and add it to the array as a new dimension the output I want should look like this

[[1, 2,  4, 7,  9, 15,  0,  0],
 [3, 4,  3, 5, 10,  2, -2, -.2857],
 [5, 6, 56, 7, 20,  1,  2, .4]]

Can this be done without a for loop? (Ok I guess it’s not efficient to do this without a for loop) But I’m still not sure how to do it with one either

Answer 1

import numpy as np
myarray = np.array([[1,2,4,7,9,15,0.0], [3, 4,3,5,10,2,-2], [5,6,56,7,20,1,2]])
#the division:
column_divs = myarray[:,-1][1:] / myarray[:,3][:-1]
#adds a 'placeholder' zero value, as the first element:
column_divs = np.hstack(([0], column_divs))
#adds the required column to the end of the array:
print np.hstack((myarray, column_divs.reshape(-1,1)))
#output:
[[  1.      2.       4.       7.       9.      15.      0.       0.        ]
 [  3.      4.       3.       5.      10.       2.     -2.      -0.28571429]
 [  5.      6.      56.       7.      20.       1.      2.      0.4        ]]