Can numpy do better than this?

[Rustom Mody]

Given a matrix I want to shift the 1st column 0 (ie leave as is)
2nd by one place, 3rd by 2 places etc.

This code works.
But I wonder if numpy can do it shorter and simpler.

---------------------
def transpose(mat):
     return([[l[i] for l in mat]for i in range(0,len(mat[0]))])
def rotate(mat):
     return([mat[i][i:]+mat[i][:i] for i in range(0, len(mat))])
def shiftcols(mat):
    return ( transpose(rotate(transpose(mat))))

>>> mat = [[1,2,3,4,5,6],
        [7,8,9,10,11,12],
        [13,14,15,16,17,18],
        [19,20,21,22,23,24],
        [25,26,27,28,29,30],
        [31,32,33,34,35,36],
        [37,38,39,40,41,42]]

>>> shiftcols(mat)

[[1, 8, 15, 22, 29, 36],
[7, 14, 21, 28, 35, 42], 
[13, 20, 27, 34, 41, 6], 
[19, 26, 33, 40, 5, 12], 
[25, 32, 39, 4, 11, 18], 
[31, 38, 3, 10, 17, 24], 
[37, 2, 9, 16, 23, 30]]


I was hoping for something like the following APL operator

>>>   mat
 1  2  3  4  5  6
 7  8  9 10 11 12
13 14 15 16 17 18
19 20 21 22 23 24
25 26 27 28 29 30
31 32 33 34 35 36
>>>   0 1 2 3 4 5 ⊖ mat
 1  8 15 22 29 36
 7 14 21 28 35  6
13 20 27 34  5 12
19 26 33  4 11 18
25 32  3 10 17 24
31  2  9 16 23 30