Try concatenating X_Yscores[:, None] (or X_Yscores[:, np.newaxis] as imaluengo suggests). This creates a 2D array out of a 1D array.

Example:

A = np.array([1, 2, 3])
print A.shape
print A[:, None].shape

Output:

(3,)
(3,1)

You can use hstack and vector broadcasting for that:

a = np.array([[1,2,3],[3,4,5],[6,7,8]])  
b = np.array([9,10,11])
res = np.hstack((a, b[:,None]))
print(res)

Output:

[[ 1  2  3  9]
 [ 3  4  5 10]
 [ 6  7  8 11]]

Note that you cannot use concatenate because the array have different shapes. hstack stack horizontally the multi-dimentional arrays so it just add a new line at the end here. A broadcast operation (b[:,None]) is needed so that the appended vector is a vertical one.

Use:

np.concatenate([a, b])

The arrays you want to concatenate need to be passed in as a sequence, not as separate arguments.

From the NumPy documentation:

numpy.concatenate((a1, a2, ...), axis=0)

Join a sequence of arrays together.

It was trying to interpret your b as the axis parameter, which is why it complained it couldn't convert it into a scalar.

In [76]: values = np.arange(16).reshape(4,4)                                                                 
In [77]: temp = np.concatenate(([0], values[1:,-1]))                                                         
In [78]: values                                                                                              
Out[78]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])
In [79]: temp                                                                                                
Out[79]: array([ 0,  7, 11, 15])

This use of concatenate to make temp is similar to your use of append (which actually uses concatenate).

Sounds like you want to join values and temp in this way:

In [80]: np.concatenate((values, temp[:,None]),axis=1)                                                       
Out[80]: 
array([[ 0,  1,  2,  3,  0],
       [ 4,  5,  6,  7,  7],
       [ 8,  9, 10, 11, 11],
       [12, 13, 14, 15, 15]])

Again I prefer using concatenate directly.