如何统计序列中元素的频度？

需求：
1、某随机序列中的[12,5,6,4,6,8,9,5]如何找到其中出现次数最高的三个元素，出现的次数是多少？
2、对某篇英文文章进行词频统计，找出出现次数最高的十个单词，它们出现的次数是多少？
思路：
1、将序列转换成字典{'元素':'频度'},根据其中的值进行排序
2、使用collections中的Count对象

代码：

# 方法一：
In [16]: from random import randint

In [17]: data = [ randint(0,20) for _ in range(30)]

In [18]: data
Out[18]: 
[10,
 17,
 1,
 17,
 6,
 17,
 12,
 19,
 13,
 5,
 18,
 19,
 14,
 8,
 12,
 19,
 9,
 9,
 11,
 1,
 0,
 4,
 6,
 0,
 4,
 9,
 17,
 2,
 8,
 4]

In [19]: d = dict.fromkeys(data,0)

In [20]: d
Out[20]: 
{10: 0,
 17: 0,
 1: 0,
 6: 0,
 12: 0,
 19: 0,
 13: 0,
 5: 0,
 18: 0,
 14: 0,
 8: 0,
 9: 0,
 11: 0,
 0: 0,
 4: 0,
 2: 0}

In [21]: for x in data:
    ...:     d[x] += 1
    ...: 

In [22]: d
Out[22]: 
{10: 1,
 17: 4,
 1: 2,
 6: 2,
 12: 2,
 19: 3,
 13: 1,
 5: 1,
 18: 1,
 14: 1,
 8: 2,
 9: 3,
 11: 1,
 0: 2,
 4: 3,
 2: 1}

In [23]: sorted([(v,k) for k,v in d.items()],reverse=True)
Out[23]: 
[(4, 17),
 (3, 19),
 (3, 9),
 (3, 4),
 (2, 12),
 (2, 8),
 (2, 6),
 (2, 1),
 (2, 0),
 (1, 18),
 (1, 14),
 (1, 13),
 (1, 11),
 (1, 10),
 (1, 5),
 (1, 2)]

In [24]: sorted([(v,k) for k,v in d.items()],reverse=True)[:3]
Out[24]: [(4, 17), (3, 19), (3, 9)]

In [25]: sorted(((v,k) for k,v in d.items()),reverse=True)[:3] # 使用生成器解析更加节省空间
Out[25]: [(4, 17), (3, 19), (3, 9)]

In [26]: import heapq

In [27]: heapq.nlargest(3,((v,k) for k,v in d.items()))
Out[27]: [(4, 17), (3, 19), (3, 9)]

# 方法二：
In [28]: from collections import Counter

In [29]: data
Out[29]: 
[10,
 17,
 1,
 17,
 6,
 17,
 12,
 19,
 13,
 5,
 18,
 19,
 14,
 8,
 12,
 19,
 9,
 9,
 11,
 1,
 0,
 4,
 6,
 0,
 4,
 9,
 17,
 2,
 8,
 4]

In [30]: Counter(data)
Out[30]: 
Counter({10: 1,
         17: 4,
         1: 2,
         6: 2,
         12: 2,
         19: 3,
         13: 1,
         5: 1,
         18: 1,
         14: 1,
         8: 2,
         9: 3,
         11: 1,
         0: 2,
         4: 3,
         2: 1})

In [31]: c = Counter(data)

In [32]: c.most_common(3)
Out[32]: [(17, 4), (19, 3), (9, 3)]

# 统计词数：
>>> txt = open('./example.txt').read()

>>> import re
>>> word_list = re.split('W+',txt)  # 以不止一个非单词字符进行切割

>>> from collections import Counter

>>> c2 = Counter(word_list)

>>> c2.most_common(10)
[('the', 18),
 ('to', 17),
 ('a', 16),
 ('it', 12),
 ('of', 12),
 ('and', 11),
 ('is', 11),
 ('that', 8),
 ('we', 8),
 ('enough', 7)]

>>>