Louis Louis - 1 month ago 11
Python Question

pythonic way to aggregate arrays (numpy or not)

I would like to make a nice function to aggregate data among an array (it's a numpy record array, but it does not change anything)

you have an array of data that you want to aggregate among one axis: for example an array of

dtype=[(name, (np.str_,8), (job, (np.str_,8), (income, np.uint32)]
and you want to have the mean income per job

I did this function, and in the example it should be called as
aggregate(data,'job','income',mean)





def aggregate(data, key, value, func):

data_per_key = {}

for k,v in zip(data[key], data[value]):

if k not in data_per_key.keys():

data_per_key[k]=[]

data_per_key[k].append(v)

return [(k,func(data_per_key[k])) for k in data_per_key.keys()]





the problem is that I find it not very nice I would like to have it in one line: do you have any ideas?

Thanks for your answer Louis

PS: I would like to keep the func in the call so that you can also ask for median, minimum...

Answer

Perhaps the function you are seeking is matplotlib.mlab.rec_groupby:

import matplotlib.mlab

data=np.array(
    [('Aaron','Digger',1),
     ('Bill','Planter',2),
     ('Carl','Waterer',3),
     ('Darlene','Planter',3),
     ('Earl','Digger',7)],
    dtype=[('name', np.str_,8), ('job', np.str_,8), ('income', np.uint32)])

result=matplotlib.mlab.rec_groupby(data, ('job',), (('income',np.mean,'avg_income'),))

yields

('Digger', 4.0)
('Planter', 2.5)
('Waterer', 3.0)

matplotlib.mlab.rec_groupby returns a recarray:

print(result.dtype)
# [('job', '|S7'), ('avg_income', '<f8')]

You may also be interested in checking out pandas, which has even more versatile facilities for handling group-by operations.