在Python 2.7(或更新版本)中，可以使用集合。计数器:

>>> import collections
>>> a = [5, 1, 2, 2, 4, 3, 1, 2, 3, 1, 1, 5, 2]
>>> counter = collections.Counter(a)
>>> counter
Counter({1: 4, 2: 4, 5: 2, 3: 2, 4: 1})
>>> counter.values()
dict_values([2, 4, 4, 1, 2])
>>> counter.keys()
dict_keys([5, 1, 2, 4, 3])
>>> counter.most_common(3)
[(1, 4), (2, 4), (5, 2)]
>>> dict(counter)
{5: 2, 1: 4, 2: 4, 4: 1, 3: 2}
>>> # Get the counts in order matching the original specification,
>>> # by iterating over keys in sorted order
>>> [counter[x] for x in sorted(counter.keys())]
[4, 4, 2, 1, 2]

如果您使用的是Python 2.6或更老版本，可以在这里下载实现。

对于一个无序列表，你应该使用:

[a.count(el) for el in set(a)]

输出为

[4, 4, 2, 1, 2]

另一种方法是使用较重但功能强大的库——NLTK。

import nltk

fdist = nltk.FreqDist(a)
fdist.values()
fdist.most_common()

通过遍历列表并计算它们，手动计算出现的数量，使用collections.defaultdict跟踪到目前为止看到的内容:

from collections import defaultdict

appearances = defaultdict(int)

for curr in a:
    appearances[curr] += 1

seta = set(a)
b = [a.count(el) for el in seta]
a = list(seta) #Only if you really want it.

num=[3,2,3,5,5,3,7,6,4,6,7,2]
print ('\nelements are:\t',num)
count_dict={}
for elements in num:
    count_dict[elements]=num.count(elements)
print ('\nfrequency:\t',count_dict)