python生成職業要求詞云

2022-07-22 07:33:11 字數 1856 閱讀 9474

接著上篇的說的，爬取了大資料相關的職位資訊，

#


-*- coding: utf-8 -*-


"""created on thu aug 10 07:57:56 2017


@author: lenovo


"""from wordcloud import


wordcloud


import


pandas as pd


import


numpy as np


import


matplotlib.pyplot as plt


import


jieba


defcloud(root,name,stopwords):


filepath = root +'


\\' +name


f = open(filepath,'


r',encoding='


utf-8')


txt =f.read()


f.close()


cut =jieba.cut(txt)


words =


for i in


cut:


df = pd.dataframe()


s= df.groupby(df['


words


'])['


words


'].agg([('


size


',np.size)]).sort_values(by='


size


',ascending=false)


s = s[~s.index.isin(stopwords['


stopword


'])].to_dict()


wordcloud = wordcloud(font_path =r'


e:\python\machine learning\simhei.ttf


',background_color='


black')


wordcloud.fit_words(s[


'size'])


plt.imshow(wordcloud)


pngfile = root +'


\\' + name.split('


.')[0] + '


.png


'wordcloud.to_file(pngfile)


import


os jieba.load_userdict(r


'e:\python\machine learning\nlpstopwords.txt')


stopwords = pd.read_csv(r'


e:\python\machine learning\stopwordscn.txt


',encoding='


utf-8


',index_col=false)


for root,dirs,file in os.walk(r'


e:\職位資訊'):


for name in


file:


if name.split('


.')[-1]=='


txt'


:            


print


(name)


cloud(root,name,stopwords)
詞云如圖所示：

可以看出有些雜訊詞沒能被去除，比如相關、以上學歷等無效詞彙。本想通過df判斷停用詞，但是我爬的時候沒顧及到這個問題，外加本身記錄數也不高，就沒再找職位資訊的停用詞。當然也可看出演算法和經驗是很重要的。加油

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