Using Python crawler to display the word cloud for the "Dunkirk" film review

Source: Internet
Author: User

Recently want to see a film, to know the review, just learning Python crawler, do a small example.

Code modified based on third-party source link

#Coding:utf-8 fromLib2to3.pgen2.grammarImport Line__author__=' Hang'ImportWarningswarnings.filterwarnings ("Ignore")ImportJieba#Word breaker PackageImportNumPy#NumPy Calculation PackageImportReImportPandas as PDImportMatplotlib.pyplot as PltImportUrllib2 fromBs4ImportBeautifulSoup as BSImportmatplotlibmatplotlib.rcparams['figure.figsize'] = (10.0, 5.0) fromWordcloudImportWordcloud#Word Cloud Pack#analyze Web page functionsdefgetnowplayingmovie_list (): Resp= Urllib2.urlopen ('') Html_data= (). Decode ('Utf-8') Soup= BS (Html_data,'Html.parser') Nowplaying_movie= Soup.find_all ('Div', id='nowplaying') Nowplaying_movie_list= Nowplaying_movie[0].find_all ('Li', class_='List-item') Nowplaying_list= []     forIteminchnowplaying_movie_list:nowplaying_dict={} nowplaying_dict['ID'] = item['Data-subject']         forTag_img_iteminchItem.find_all ('img'): nowplaying_dict['name'] = tag_img_item['alt'] Nowplaying_list.append (nowplaying_dict)returnnowplaying_list#Crawl Comment FunctiondefGetcommentsbyid (MovieID, pagenum): Eachcommentstr="'    ifPagenum>0:start= (pageNum-1) * 20Else:        returnFalse Requrl=''+ MovieID +'/comments'+'?'+'start='+ str (START) +'&limit=20'    Print(requrl) Resp=Urllib2.urlopen (requrl) () Soup= BS (Html_data,'Html.parser') Comment_div_lits= Soup.find_all ('Div', class_='Comment')     forIteminchcomment_div_lits:ifItem.find_all ('P') [0].string is  notNone:eachcommentstr+=item.find_all ('P') [0].stringreturnEachcommentstr.strip ()defMain ():#cycle to get the first 10 pages of a movie reviewCommentstr ="'nowplayingmovie_list=getnowplayingmovie_list () forIinchRange (10): Num= i + 1commentlist_temp= Getcommentsbyid (nowplayingmovie_list[0]['ID'], num) commentstr+=Commentlist_temp.strip ()#Print CommentsCleaned_comments = Re.sub ("[\s+\.\!\/_,$%^* (+\ "\ ')]+| [+--()? "", "<> ,...。? , [email protected]#¥%......&* ()]+","", Commentstr)Printcleaned_comments#using stuttering participle for Chinese word segmentationsegment=jieba.lcut (cleaned_comments) WORDS_DF=PD. DataFrame ({'segment': Segment}) #Remove the Stop wordStopwords=pd.read_csv ("D:\pycode\stopwords.txt", index_col=false,quoting=3,sep="\ t", names=['Stopword'], encoding='Utf-8')#quoting=3 all not quotedwords_df=words_df[~Words_df.segment.isin (Stopwords.stopword)]PrintWORDS_DF#Statistical FrequencyWords_stat=words_df.groupby (by=['segment'])['segment'].agg ({"Count": Numpy.size}) Words_stat=words_stat.reset_index (). Sort_values (by=["Count"],ascending=False)#display with a word cloudWordcloud=wordcloud (font_path="D:\pycode\simhei.ttf", background_color=" White", max_font_size=80) Word_frequence= {X[0]:x[1] forXinchWords_stat.head (1000). Values} word_frequence_list= []     forKeyinchword_frequence:temp=(Key,word_frequence[key]) word_frequence_list.append (temp) Wordcloud=wordcloud.fit_words (Dict (word_frequence_list)) plt.imshow (Wordcloud) Plt.axis ("if") ()#Main functionMain ()

Using Python crawler to display the word cloud for the "Dunkirk" film review

Related Article

Contact Us

The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion; products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the content of the page makes you feel confusing, please write us an email, we will handle the problem within 5 days after receiving your email.

If you find any instances of plagiarism from the community, please send an email to: and provide relevant evidence. A staff member will contact you within 5 working days.

A Free Trial That Lets You Build Big!

Start building with 50+ products and up to 12 months usage for Elastic Compute Service

  • Sales Support

    1 on 1 presale consultation

  • After-Sales Support

    24/7 Technical Support 6 Free Tickets per Quarter Faster Response

  • Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.