Rapid compression of multiple lists with value addition

I am looking for a pythonic way to iterate through a large number of lists and use the index of repeated values from one list to calculate a total value from the values with the same index in another list.

For example, say I have two lists

a = [ 1, 2, 3, 1, 2, 3, 1, 2, 3]
b = [ 1, 2, 3, 4, 5, 6, 7, 8, 9]

What I want to do is find the unique values in a, and then add together the corresponding values from b with the same index. My attempt, which is quite slow, is as follows:

a1=list(set(a))
b1=[0 for y in range(len(a1))] 
    for m in range(len(a)):
        for k in range(len(a1)):
            if a1[k]==a[m]:
                b1[k]+=b[m]

and I get

a1=[1, 2, 3]
b1=[12, 15, 18]

Please let me know if there is a faster, more pythonic way to do this. Thanks

Using numpy this becomes really easy. You could do:

import numpy as np

a = np.array([1,1,3,5,5,6,8,8,9])
b = np.array([2,3,4,5,6,7,8,9,0])
_, indices = np.unique(a, retu_index=True)
c = a[indices] + b[indices]

Use the zip() function and a defaultdict dictionary to collect values per unique value:

from collections import defaultdict
try:
    # Python 2 compatibility
    from future_builtins import zip
except ImportError:
    # Python 3, already there
    pass

values = defaultdict(int)
for key, value in zip(a, b):
    values[key] += value

a1, b1 = zip(*sorted(values.items()))

zip() pairs up the values from your two input lists, now all you have to do is sum up each value from b per unique value of a.

The last line pulls out the keys and values from the resulting dictionary, sorts these, and puts just the keys and just the values into a1 and b1, respectively.

Demo:

>>> from collections import defaultdict
>>> a = [ 1, 2, 3, 1, 2, 3, 1, 2, 3]
>>> b = [ 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> values = defaultdict(int)
>>> for key, value in zip(a, b):
...     values[key] += value
...
>>> zip(*sorted(values.items()))
[(1, 2, 3), (12, 15, 18)]