词频统计

Posted 2020-10-28 阿yuan

下载一首英文的歌词或文章

将所有,.？！’:等分隔符全部替换为空格

将所有大写转换为小写

生成单词列表

生成词频统计

排序

排除语法型词汇，代词、冠词、连词

输出词频最大TOP20

将分析对象存为utf-8编码的文件，通过文件读取的方式获得词频分析内容。

f=open(\'new.txt\',\'r\')
str0 = f.read();
f.close();
str1 = \'\'\',.\'?!"\'\'\';
for i in str1:
    list1 = str0.replace(i,\' \');
list1 = str0.lower().split();

gath2={\'in\',\'to\',\'your\',\'you\',\'and\',\'the\',\'for\'};

gath=set(list1)-gath2;
print(gath)
#字典
dict={}
for w in gath:
    dict[w]=list1.count(w)

list1 = list(dict.items())
list1.sort(key=lambda x:x[1],reverse=True)
print(list1)

f=open(\'newscount.txt\',\'a\')
for i in range(25):
    f.write(list1[i][0]+\' \'+str(list1[i][1])+\'\\n\')
f.close()

运行结果：

[(\'be\', 8), (\'one\', 8), (\'a\', 8), (\'wanna\', 6), (\'not\', 6), (\'or\', 5), (\'can\', 5), (\'just\', 5), (\'that\', 4), (\'president\', 3), (\'know\', 3), (\'actor\', 3), (\'we\', 3), (\'lawyer\', 3), (\'all\', 3), (\'singerwhy\', 3), (\'dreameryou\', 3), (\'could\', 2), (\'manyou\', 2), (\'bepolice\', 2), (\'manwhy\', 2), (\'old\', 2), (\'fighter\', 2), (\'like\', 2), (\'this\', 2), (\'got\', 2), (\'something\', 2), (\'what\', 2), (\'really\', 2), (\'man\', 2), (\'life\', 2), (\'post\', 2), (\'fire\', 2), (\'on\', 2), (\'foryou\', 1), (\'it\', 1), (\'matterwe\', 1), (\'matterluxury\', 1), (\'live\', 1), (\'real\', 1), (\'cars\', 1), (\'caught\', 1), (\'ways\', 1), (\'reach\', 1), (\'lifefocus\', 1), (\'team\', 1), (\'nice\', 1), (\'does\', 1), ("that\'s", 1), ("thingthat\'s", 1), (\'of\', 1), (\'little\', 1), (\'play\', 1), ("doesn\'t", 1), (\'medoctor\', 1), (\'topmake\', 1), (\'dream\', 1), (\'fori\', 1), (\'may\', 1), ("bring\'cause", 1), (\'foreverjust\', 1), (\'nothing\', 1), (\'every\', 1), (\'steam\', 1), (\'lasts\', 1), (\'bedoctor\', 1), (\'up\', 1), (\'bei\', 1), (\'hold\', 1), (\'bewe\', 1), (\'doctor\', 1), (\'never\', 1), (\'thingthat\', 1), (\'different\', 1), (\'have\', 1), (\'stopbe\', 1), (\'sure\', 1), (\'benow\', 1), (\'share\', 1), (\'thinkbut\', 1), (\'with\', 1), (\'bling\', 1), ("won\'t", 1), (\'sing\', 1), (\'togetherwe\', 1)]

2.中文词频统计：

下载一长篇中文文章。

从文件读取待分析文本。

news = open(\'gzccnews.txt\',\'r\',encoding = \'utf-8\')

安装与使用jieba进行中文分词。

pip install jieba

import jieba

list(jieba.lcut(news))

生成词频统计

排序

排除语法型词汇，代词、冠词、连词

输出词频最大TOP20（或把结果存放到文件里）

import jieba
f=open(\'xiyouji.txt\',\'r\',encoding=\'utf-8\')
result = f.read()
f.close();
str1 = \'\'\'，。‘’“”：；（）！？、 \'\'\'
dele = {\'我\', \'道\', \'不\', \'一\', \'了\', \'那\', \'是\', \'来\', \'他\', \'个\', \'行\', \'你\', \'的\',
     \'者\',\'有\',\'\\n\',\'-\',\'出\'}
jieba.add_word(\'三藏\')
jieba.add_word(\'孙行者\')
jieba.add_word(\'猴王\')

for i in str1:
    result = result.replace(i, \'\')

tempwords = list(jieba.cut(result))
count = {}
words = list(set(tempwords) - dele)

for i in range(0, len(words)):
    count[words[i]] = result.count(str(words[i]))

countList = list(count.items())
countList.sort(key=lambda x: x[1], reverse=True)
print(countList)

f = open(\'baocun.txt\', \'a\',encoding=\'utf-8\')
for i in range(30):
    f.write(countList[i][0] + \':\' + str(countList[i][1]) + \'\\n\')
f.close()

运行结果：