You want vstack:

In [45]: a = np.array([[1,2,3]])

In [46]: l = [4,5,6]

In [47]: np.vstack([a,l])
Out[47]: 
array([[1, 2, 3],
       [4, 5, 6]])

You can stack multiple rows on the condition that The arrays must have the same shape along all but the first axis.

In [53]: np.vstack([a,[[4,5,6], [7,8,9]]])
Out[53]: 
array([[1, 2, 3],
       [4, 5, 6],
       [4, 5, 6],
       [7, 8, 9]])

Use np.empty to initialize an empty array and define the axis you want to append across:

import numpy as np
mat = np.empty((0,2))
for i in np.arange(3):
    val = np.random.rand(2, 2)
    mat = np.append(mat,val, axis=0)
print(mat)

Output:

[[0.08527627 0.40567273]
 [0.39701354 0.72642426]
 [0.17540761 0.02579183]
 [0.76271521 0.83032347]
 [0.08105248 0.67986726]
 [0.48079453 0.37454798]]

However, as stated in my comment, if you need to append a lot of times you should look into initializing an array of the correct size then assigning values over using np.append() or appending to a list instead (if you do not know the size of the array) and then creating a numpy array after

In [1]: import numpy as np

In [2]: a = np.array([[1, 2, 3], [4, 5, 6]])

In [3]: b = np.array([[9, 8, 7], [6, 5, 4]])

In [4]: np.concatenate((a, b))
Out[4]: 
array([[1, 2, 3],
       [4, 5, 6],
       [9, 8, 7],
       [6, 5, 4]])

or this:

In [1]: a = np.array([1, 2, 3])

In [2]: b = np.array([4, 5, 6])

In [3]: np.vstack((a, b))
Out[3]: 
array([[1, 2, 3],
       [4, 5, 6]])

As the error indicate, the dimensions have to match.

So you could resize a so that it matches the dimension of b and then concatenate (the empty cells are filled with zeros).

a.resize(3,4)
a = a.transpose()
np.concatenate((a,b))

array([[ 1,  0,  0],
       [ 2,  0,  0],
       [ 3,  0,  0],
       [ 4,  0,  0],
       [ 4,  5,  6],
       [ 7,  8,  9],
       [10, 11, 12]])

Nest the arrays so that they have more than one axis, and then specify the axis when using append.

import numpy as np
a = np.array([[1, 2]]) # note the braces
b = np.array([[3, 4]])
c = np.array([[5, 6]])

d = np.append(a, b, axis=0)
print(d)
# [[1 2]
#  [3 4]]

e = np.append(d, c, axis=0)
print(e)
# [[1 2]
#  [3 4]
#  [5 6]]

Alternately, if you stick with lists, use numpy.vstack:

import numpy as np
a = [1, 2]
b = [3, 4]
c = [5, 6]

d = np.vstack([a, b])
print(d)
# [[1 2]
#  [3 4]]

e = np.vstack([d, c])
print(e)
# [[1 2]
#  [3 4]
#  [5 6]]