标签：... comm when 随机 词频统计 split rand ons 序列
统计序列中元素出现的频度
案例1：
随机序列[1,2,3,4,44,2,3,8...]中，找出次数出现最高的3个元素，并统计他们出现的次数。
# eg_v1
from random import randint
data = [randint(1, 20) for _ in range(30)]
print(data)
# [19, 15, 4, 18, 18, 7, 18, 13, 18, 20, 18, 3, 5, 6, 7, 19, 2, 15, 3, 6, 13, 4, 14, 20, 1, 18, 13, 2, 11, 4]
c = dict.fromkeys(data,0)
for x in data:
c[x] += 1
print (c)
# {1: 1, 2: 2, 3: 2, 4: 3, 5: 1, 6: 2, 7: 2, 11: 1, 13: 3, 14: 1, 15: 2, 18: 6, 19: 2, 20: 2}
d = sorted(c.items(),key= lambda asd:asd[1])
print (d)
# [(1, 1), (5, 1), (11, 1), (14, 1), (2, 2), (3, 2), (6, 2), (7, 2), (15, 2), (19, 2), (20, 2), (4, 3), (13, 3), (18, 6)]
# eg_v2 使用字典中collections.Counter 方法
"""
将序列传入Counter的构造器，得到Counter方法就是元素词频的字典
Counter.most_common(n) 方法得到最高的n个元素的列表
"""
from random import randint
from collections import Counter
data = [randint(1, 20) for _ in range(30)]
print (data)
# [5, 13, 2, 9, 9, 20, 10, 9, 1, 14, 10, 1, 9, 12, 14, 3, 8, 20, 10, 7, 10, 4, 7, 18, 15, 10, 17, 5, 5, 16]
c2 = Counter(data)
print (c2)
# Counter({10: 5, 9: 4, 5: 3, 1: 2, 7: 2, 14: 2, 20: 2, 2: 1, 3: 1, 4: 1, 8: 1, 12: 1, 13: 1, 15: 1, 16: 1, 17: 1, 18: 1})
n = c2.most_common(3)
print (n)
# [(10, 5), (9, 4), (5, 3)]
案例2：
对某英文文章的单词进行词频统计，找出出现次数最多的10个单词，它们出现的次数是多少。
import re
from collections import Counter
file_txt = open("Alice.txt").read()
# print (file_txt)
rst = re.split("\s",file_txt) # 匹配任何空白字符，包括空格、制表符、换页符等。与 [ \f\n\r\t\v] 等效
# print(rst)
c3 = Counter(rst)
# print (c3)
c4 = c3.most_common(10)
print (c4)
# [(‘I‘, 31), (‘the‘, 13), ("I‘ll", 11), (‘When‘, 8), (‘stop‘, 6), (‘down‘, 6), (‘me‘, 5), (‘myself‘, 5), (‘get‘, 5), (‘to‘, 5)]
标签：... comm when 随机 词频统计 split rand ons 序列
原文地址：http://www.cnblogs.com/xieshengsen/p/7190137.html
