Im trying to find the largest difference between i and j in a series where i cannot be before j. Is there an efficient way to do this in pandas:

x = [1, 2, 5, 4, 2, 4, 2, 1, 7]
largest_change = 0for i in range(len(x)):for j in range(i+1, len(x)):change = x[i] - x[j]print(x[i], x[j], change)if change > largest_change:largest_change = change

The output would just be the value, in this case 4 from 5 to 1.

Try numpy broadcast with np.triu and max

arr = np.array(x)
np.triu(arr[:,None] - arr)array([[ 0, -1, -4, -3, -1, -3, -1,  0, -6],[ 0,  0, -3, -2,  0, -2,  0,  1, -5],[ 0,  0,  0,  1,  3,  1,  3,  4, -2],[ 0,  0,  0,  0,  2,  0,  2,  3, -3],[ 0,  0,  0,  0,  0, -2,  0,  1, -5],[ 0,  0,  0,  0,  0,  0,  2,  3, -3],[ 0,  0,  0,  0,  0,  0,  0,  1, -5],[ 0,  0,  0,  0,  0,  0,  0,  0, -6],[ 0,  0,  0,  0,  0,  0,  0,  0,  0]])np.triu(arr[:,None] - arr).max()Out[758]: 4