How can I add an additional row and column to an array?

I assume your column and rows are just a list of lists?

That is, you have the following?

L = [[1,2,3],
     [4,5,6]]

To add another row, use the append method of a list.

L.append([7,8,9])

giving

L = [[1,2,3],
     [4,5,6],
     [7,8,9]]

To add another column, you would have to loop over each row. An easy way to do this is with a list comprehension.

L = [x + [0] for x in L]

giving

L = [[1,2,3,0],
     [4,5,6,0]]

I would suggest sympy Matrix object to do it:

a = [[ 2,   1,  180],
     [ 1,   3,  300],
     [-1,  -4,    0]]

b = [[1,0],
     [0,0],
     [0,1]]

import sympy as sp

a = sp.Matrix(a).col_insert(-2, sp.Matrix(b))
a.tolist()

Output:

[[2, 1, 0, 1, 180], 
 [1, 0, 0, 3, 300], 
 [-1, 0, 1, -4, 0]]

And to continue with a Numpy array, you can use np.asarray(a) instead of a.tolist() (assuming you have imported Numpy as np)

There are many ways to do this in numpy, but not all of them let you add the row/column to the target array at any location (e.g., append only allows addition after the last row/column). If you want a single method/function to append either a row or column at any position in a target array, i would go with 'insert':

T = NP.random.randint(0, 10, 20).reshape(5, 4)
c = NP.random.randint(0, 10, 5)
r = NP.random.randint(0, 10, 4)
# add a column to T, at the front:
NP.insert(T, 0, c, axis=1)
# add a column to T, at the end:
NP.insert(T, 4, c, axis=1)
# add a row to T between the first two rows:
NP.insert(T, 2, r, axis=0)