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python数据结构-如何统计序列中元素的频度
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如何统计序列中元素的频度
问题举例
如何找出随机序列[1, 5, 6, 5, 3, 2, 1, 0, 6, 1, 6]中出现频度最高的3个元素？
如何统计某篇英文文章中词频最高的5个单词？
将序列转换成字典（元素：频度），根据字典的值进行排序
列表
from random import randint
list1 = [randint(0, 10) for _ in range(30)]
print(list1)
dict1 = dict.fromkeys(list1, 0)
for item in list1:
dict1[item] += 1#list comprehensions
dict_res1 = sorted([(v, k) for k, v in dict1.items()], reverse=True)[:3]
print(dict_res1)#generator comprehensions
dict_res2 = sorted(((v, k) for k, v in dict1.items()), reverse=True)[:3]
print(dict_res2)
分析：使用生成器解析比列表解析节省空间
当一个列表很大时，我们只需要找到出现频度最高的3个元素，如果我们对整个列表都进行排序，
这样显然是很浪费的，一般这种情况我们会使用堆排序
堆排序
from random import randint
import heapqlist1 = [randint(0, 10) for _ in range(30)]
print(list1)
dict1 = dict.fromkeys(list1, 0)
for item in list1:
dict1[item] += 1res = heapq.nlargest(3, ((v, k) for k, v in dict1.items()))
print(res)
使用collections中的Counter对象from random import randint
from collections import Counterlist1 = [randint(0, 10) for _ in range(30)]
print(list1)
dict1 = dict.fromkeys(list1, 0)
for item in list1:
dict1[item] += 1counter1 = Counter(dict1)
res = counter1.most_common(3)
print(res)
from random import randint
from collections import Counterlist1 = [randint(0, 10) for _ in range(30)]
print(list1)
dict1 = dict.fromkeys(list1, 0)
for item in list1:
dict1[item] += 1counter1 = Counter(dict1)
res = counter1.most_common(3)
print(res)
词频统计栗子
import re
from collections import Countertxt = open('note.txt').read()
word_list = re.split('\W+', txt)counter1 = Counter(word_list)
res = counter1.most_common(3)
print(res)
参考资料：python3实用编程技巧进阶
