中文词频统计及词云制作

1.中软国际华南区技术总监曾老师还会来上两次课，同学们希望曾老师讲些什么内容？（认真想一想回答）

答：展示一些使用python技术进行的实际项目（不违反公司规定下）。

2.中文分词

1. 下载一中文长篇小说，并转换成UTF-8编码。 

 

      2. 使用jieba库，进行中文词频统计，输出TOP30的词及出现次数。

import jieba
txt = open("雪中悍刀行.txt","r",encoding='utf-8').read()
a = jieba.cut(txt)
counts = {}

for b in a:
    if len(b) == 1:
        continue
    else:
        counts[b] = counts.get(b,0) + 1
items = list(counts.items())
items.sort(key=lambda x:x[1],reverse=True)

for i in range(30):
    b,count = items[i]
    print("{0:<6}{1:>3}".format(b,count))

 

   3.排除一些词、合并同一词。

import jieba
txt = open("雪中悍刀行.txt","r",encoding='utf-8').read()

ex = {"女子",'袁庭山','江南','仙侠','年轻','丫鬟','武当山','古剑'}
a = jieba.cut(txt)
counts = {}

for b in a:
    if len(b) == 1:
        continue
    else:
        counts[b] = counts.get(b,0) + 1
for a in ex:
    del(counts[a])

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

for i in range(30):
    b,count = items[i]
    print("{0:<6}{1:>3}".format(b,count))

      4.使用wordcloud库绘制一个词云。

from wordcloud import WordCloud

import matplotlib.pyplot as plt

txt = open('雪中.txt','r',encoding = 'utf-8').read()

mywc = WordCloud().generate(txt)

plt.imshow(mywc)
plt.axis("off")
plt.show()