计算第一个数字相似的所有元组值的平均值

Posted 2021-04-09

考虑元组列表

[(7751, 0.9407466053962708), (6631, 0.03942129), (7751, 0.1235432)]

如何以第一个数字相似的pythonic方式计算所有元组值的平均值？例如答案必须是

[(7751, 0.532144902698135), (6631, 0.03942129)]

答案

一种方法是使用collections.defaultdict

from collections import defaultdict
lst = [(7751, 0.9407466053962708), (6631, 0.03942129), (7751, 0.1235432)]
d_dict = defaultdict(list)
for k,v in lst:
    d_dict[k].append(v)

[(k,sum(v)/len(v)) for k,v in d_dict.items()]
#[(7751, 0.5321449026981354), (6631, 0.03942129)]

另一答案

你用groupby，

from itertools import groupby
result = []
for i,g in groupby(sorted(lst),key=lambda x:x[0]):
    grp = list(g)
    result.append((i,sum(i[1] for i in grp)/len(grp)))

使用，list comprehension，

def get_avg(g):
    grp = list(g)
    return sum(i[1] for i in grp)/len(grp)

result = [(i,get_avg(g)) for i,g in groupby(sorted(lst),key=lambda x:x[0])]

结果

[(6631, 0.03942129), (7751, 0.5321449026981354)]

另一答案

来自groupby的itertools是你的朋友：

>>> l=[(7751, 0.9407466053962708), (6631, 0.03942129), (7751, 0.1235432)] 

>>> #importing libs:
>>> from itertools import groupby
>>> from statistics import mean              #(only python >= 3.4)
>>> # mean=lambda l: sum(l) / float(len(l))  #(for python < 3.4) (*1)

>>> #set the key to group and sort and sorting
>>> k=lambda x: x[0]         
>>> data = sorted(l, key=k)  

>>> #here it is, pythonic way:
>>> [ (k, mean([m[1] for m in g ])) for k, g in groupby(data, k) ] 

结果：

[(6631, 0.03942129), (7751, 0.5321449026981354)]

编辑（* 1）感谢Elmex80s将我推荐给mean。