中文词云代码调试

词云是个很有意思的东西。

中文词云代码调试,中文调试

词云是个很有意思的东西。

用jieba断词,小说文本存入”mori.txt”,停用词列表在”stopword.txt”中,断词结果好坏,停用词很重要,需要不断调整补充。

from wordcloud import WordCloud
import jieba

f = open(u'mori.txt','r').read()
##cuttext=" ".join(jieba.cut(f))
cuttext= jieba.cut(f) 
final= [] 
stopwords=open(u'stopword.txt','r').read() 

for seg in cuttext:
    ##seg = seg.encode('utf-8')
    if seg[0] not  in ['0','1','2','3','4','5','6','7','8','9']:##忽略数字
        if seg not in stopwords:
            final.append( seg) ## 列表添加   

font=r"c:/Windows/Fonts/simsun.ttc"##中文显示必须加
wordcloud = WordCloud(font_path=font,background_color="white",width=1000, height=860, margin=2).generate(" ".join(final))

import matplotlib.pyplot as plt
plt.imshow(wordcloud)
plt.axis("off")
plt.show()

  wordcloud.to_file(‘test.png’)

效果图:

图片 1

下面是词频统计排序,词长排序的代码。

##统计词频
freqD2 = {}
for word2 in final:
  freqD2[word2] = freqD2.get(word2, 0) + 1 

##按词频排序输出
counter_list = sorted(freqD2.items(), key=lambda x: x[1], reverse=True) 
_2000=counter_list[0][1] + 1
print(_2000)##用于词长词频排序用
fp = open('sort.txt',"w+",encoding='utf-8')
for d in counter_list:
  fp.write(d[0]+':'+str(d[1]))
  fp.write('\n')
fp.close()

##按词长词频排序输出
counter_list = sorted(freqD2.items(), key=lambda x: len(x[0])*_2000+x[1], reverse=True) 
fp = open('sortlen.txt',"w+",encoding='utf-8')
for d in counter_list:
  fp.write(d[0]+':'+str(d[1]))
  fp.write('\n')
fp.close()

排序代码很方便,也值得借鉴,Python是个好东西,强大,易重用。

 

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词云是个很有意思的东西。
用jieba断词,小说文本存入”mori.txt”,停用词列表在”stopword.txt”中,断词结果好坏,…

用jieba断词,小说文本存入”mori.txt”,停用词列表在”stopword.txt”中,断词结果好坏,停用词很重要,需要不断调整补充。

from wordcloud import WordCloud
import jieba

f = open(u'mori.txt','r').read()
##cuttext=" ".join(jieba.cut(f))
cuttext= jieba.cut(f) 
final= [] 
stopwords=open(u'stopword.txt','r').read() 

for seg in cuttext:
    ##seg = seg.encode('utf-8')
    if seg[0] not  in ['0','1','2','3','4','5','6','7','8','9']:##忽略数字
        if seg not in stopwords:
            final.append( seg) ## 列表添加   

font=r"c:/Windows/Fonts/simsun.ttc"##中文显示必须加
wordcloud = WordCloud(font_path=font,background_color="white",width=1000, height=860, margin=2).generate(" ".join(final))

import matplotlib.pyplot as plt
plt.imshow(wordcloud)
plt.axis("off")
plt.show()

  wordcloud.to_file(‘test.png’)

效果图:

图片 1

下面是词频统计排序,词长排序的代码。

##统计词频
freqD2 = {}
for word2 in final:
  freqD2[word2] = freqD2.get(word2, 0) + 1 

##按词频排序输出
counter_list = sorted(freqD2.items(), key=lambda x: x[1], reverse=True) 
_2000=counter_list[0][1] + 1
print(_2000)##用于词长词频排序用
fp = open('sort.txt',"w+",encoding='utf-8')
for d in counter_list:
  fp.write(d[0]+':'+str(d[1]))
  fp.write('\n')
fp.close()

##按词长词频排序输出
counter_list = sorted(freqD2.items(), key=lambda x: len(x[0])*_2000+x[1], reverse=True) 
fp = open('sortlen.txt',"w+",encoding='utf-8')
for d in counter_list:
  fp.write(d[0]+':'+str(d[1]))
  fp.write('\n')
fp.close()

排序代码很方便,也值得借鉴,Python是个好东西,强大,易重用。