saving an ordered pair from a list of numbers using python -

i have array of numbers:

q1a = [1,2,2,2,4,3,1,3,3,4,0,0] 

i want save these in array stored in (number, proportion of number) using python.

such : [[0 0.1667], [1 0.1667], [2 0.25], [3 0.25], [4 0.167]].

this essential calculate distribution of numbers. how can this?

although wrote code save numbers : (number, number of times occurred in list) cant figure out how can find proportion of each number. thanks.

sorted_sample_values_of_x = unique, counts = np.unique(q1a, return_counts=true) np.asarray((unique, counts)).t np.put(q1a, [0], [0])  sorted_x = np.matrix(sorted_sample_values_of_x) sorted_x = np.transpose(sorted_x) print('\n' 'values of x (sorted):' '\n') print(sorted_x) 

you need 2 things.

1. convert sorted_x array float array.

2. and divide sum of counts array.

example -

in [34]: sorted_x = np.matrix(sorted_sample_values_of_x)  in [35]: sorted_x = np.transpose(sorted_x).astype(float)  in [36]: sorted_x out[36]: matrix([[ 0.,  2.],         [ 1.,  2.],         [ 2.,  3.],         [ 3.,  3.],         [ 4.,  2.]])  in [37]: sorted_x[:,1] = sorted_x[:,1]/counts.sum()  in [38]: sorted_x out[38]: matrix([[ 0.        ,  0.16666667],         [ 1.        ,  0.16666667],         [ 2.        ,  0.25      ],         [ 3.        ,  0.25      ],         [ 4.        ,  0.16666667]]) 

to store numbers propertions in new array, -

in [41]: sorted_x = np.matrix(sorted_sample_values_of_x)  in [42]: sorted_x = np.transpose(sorted_x).astype(float)  in [43]: ns = sorted_x/np.array([1,counts.sum()])  in [44]: ns out[44]: matrix([[ 0.        ,  0.16666667],         [ 1.        ,  0.16666667],         [ 2.        ,  0.25      ],         [ 3.        ,  0.25      ],         [ 4.        ,  0.16666667]])