Get max values based on unique values in another list - python

[Antonio]

In a numpy.ndarray (2d) I want to calculate the maximum of corresponding values (second column) of repetitive values (first column) in the array. Like if the array is this:

sys_func = 

array([[126.        ,   4],
           [126.        ,  11],
           [126.        ,   2],
           [126.        ,  12],
           [126.        ,  23],
           [126.        ,   1],
           [129.        ,  11],
           [129.        ,  45],
           [129.        ,   3],
           [129.        , 125],
           [129.        ,  54],
           [129.        ,   1],
           [129.        ,   1],
           [129.        ,  53],
           [132.        ,  41],
           [132.        ,   1],
           [132.        ,   2],
           [142.        ,   6],
           [142.        ,  76        ]])

unique_days = [int(x) for x in np.unique(sys_func[:,0])]

I want to get this:

[126 23;
129 125;
132 41;
142 76]

I have tried the following:

max_sr = []
for i in range(len(unique_days)):
    s = [max(sys_func[:,1]) for x in np.where(sys_func[:,0] == unique_days[i])]
    max_sr.append(s)

and it's obv giving me the wrong answer! Any ideas how to fix this?