from collect import crawler from analysis import analizer from visualize import visualizer pagename = "jtbcnews" from_date = "2018-05-01" to_date = "2018-05-24" if __name__ == "__main__": # postList = crawler.fb_get_post_list(pagename, from_date, to_date) # print(postList) dataString = analizer.json_to_str("D:/fb/jtbcnews.json", 'comments_str') count_data = analizer.count_wordfreq(dataString) print(count_data.most_common(20)) # most_common(20) 상위 20위까지만 표시하게끔 해줌 # dictWords = dict(count_data.most_common(20)) # visualizer.show_graph_bar(dictWords, pagename) dictWords = dict(count_data.most_common(20)) visualizer.wordcloud(dictWords, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer pagename = "chosun" from_date = "2018-05-22" to_date = "2018-05-24" if __name__ == "__main__": # #수집 # postList = crawler.fb_get_post_list(pagename,from_date,to_date) # print(postList) #분석 dataString = analizer.json_to_str("D:/JavaStudy/imformation/chosun.json", "message_str") count_data = analizer.count_wordfreq(dataString) print(count_data) dictword = dict(count_data.most_common(20)) # 그래프 visualizer.show_graph_bar(dictword, pagename) # 워드클라우드 visualizer.wordcloud(dictword, pagename)
from analysis.analizer import json_to_str, count_wordfreq from collect.crawler import fb_get_post_list from visualize.visualizer import show_gragh_bar, word_cloud pagename = "BlizzHeroesKR" # pagename = "WarcraftKR" # pagename = "BlizzardKR" # pagename = "jtbcnews" # pagename = "chosun" from_date = "2016-10-10" to_date = "2018-05-23" file_path = "D:/Bigdata/facebook/%s.json" % pagename if __name__ == '__main__': #수집 fb_get_post_list(pagename, from_date, to_date) #분석 data_string = json_to_str(file_path, "message_str") count_data = count_wordfreq(data_string) dict_word = dict(count_data.most_common(35)) #그래프 show_gragh_bar(dict_word, pagename) word_cloud(dict_word, pagename)
from collect import crawler as cr from analysis import analizer as an from visualize import visualizer as vi import simplejson pagename = "TheHeraldBusiness" from_date = "2018-04-01" to_date = "2018-05-29" if __name__ == "__main__": #수집 postList = cr.fb_get_post_list(pagename, from_date, to_date) print(postList) #분석 dataString = an.json_to_str( "/Users/WOOSEUNGMI/Desktop/2018/javaStudy/facebook/TheHeraldBusiness.json", "message_str") # 파일경로+경로명, key값(dic의) count_data = an.count_wordfreq(dataString) print(count_data) #어떤 단어를 몇번 이용했는지 출력 #리스트를 딕셔너리 형태로 변경 dictWord = dict(count_data.most_common(20)) #단어 상위 몇개만 지정 #그래프 vi.show_graph_bar(dictWord, pagename) #폰트네임알아내기 # 워드크라우드 vi.wordcloud(dictWord, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer pagename = "tvchosunnews" from_date = "2017-01-01" to_date = "2018-10-31" if __name__=="__main__": # 수집 postList = crawler.fb_get_post_list(pagename, from_date, to_date) print(postList) #분석 dataString = analizer.json_to_str("D:/javaStudy/facebook/jtbcnews.json", "message_str") count_data = analizer.count_wordfreq(dataString) print(count_data) dictWord = dict(count_data.most_common(40)) # 그래프 visualizer.show_graph_bar(dictWord, pagename) visualizer.wordcloud(dictWord, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer #pagename = "jtbcnews" pagename = "chosun" from_date = "2017-01-01" to_date = "2017-10-31" if __name__ == '__main__': #수집 저장 postList = crawler.fb_get_post_list(pagename, from_date, to_date) print(postList) #분석 datastring = analizer.json_to_str("D:/spring/fb/%s.json" % pagename, "message_str") count_data = analizer.count_wordfreq(datastring) print(count_data) #list 데이터를 가지고 그림을 그릴것이다.ㅋㅋ dictWord = dict(count_data.most_common(20)) #list 딕셔너리 형태로 형변환 #그래프 visualizer.show_graph_bar(dictWord, pagename) #워드크라우드 visualizer.worldcloud(dictWord, pagename)
from visualize import visualizer pagename = "chosun" from_date = "2017-01-01" to_date = "2018-05-23" path = "D:/javaStudy/" f_ex = ".json" filename = path + pagename + f_ex if __name__ == "__main__": # 수집 # postList = crawler.fb_get_post_list(pagename, from_date, to_date) # print(postList) # 분석 dataString = analizer.json_to_str(filename, "message_str") count_data = analizer.count_wordfreq(dataString) # with open("d:/javaStudy/analysis_" + f_name + ".json", 'w', encoding='utf-8') as outfile: # json_string = json.dumps(count_data, indent=4, sort_keys=True, ensure_ascii=False) # outfile.write(json_string) print("카운트데이터 : ", count_data) dictWord1 = dict(count_data.most_common(20)) dictWord2 = dict(count_data.most_common(50)) # 그래프 visualizer.show_graph_bar(dictWord1, pagename) visualizer.wordcloud(dictWord2, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer pagename = "chosun" from_date = "2018-02-09" to_date = "2018-02-30" if __name__ == "__main__": # 수집 result = crawler.fb_get_post_list(pagename, from_date, to_date) print(result) # 분석 dataString = analizer.json_to_str("D:\javaStudy/facebook/chosun.json", "message") # print(dataString) dictWords = analizer.count_wordfreq(dataString) #count_data = analizer.count_wordfreq(dataString) #print(count_data) #dictWords = dict(count_data.most_common(20)) print(type(dictWords)) print(dictWords) # 그래프 visualizer.show_graph_bar(dictWords, pagename) visualizer.wordcloud(dictWords, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer pagename = "chosun" from_date = "2018-05-01" to_date = "2018-05-24" if __name__=="__main__": #수집 result=crawler.fb_get_post_list(pagename,from_date,to_date) print(result) #분석 dataString = analizer.json_to_str("d:/" + pagename + ".json", 'message_str') data = analizer.count_wordfreq(dataString) dictWords = dict(data.most_common(20)) print(data) #그래프 visualizer.show_graph_bar(dictWords,pagename) #워드클라우드 visualizer.wordcloud(dictWords, pagename)
from collect import crawler from analysis import analizer from visualize import visualizer pagename = "channelanews" from_date = "2018-05-30" to_date = "2018-05-31" if __name__ == "__main__": #수집 postList = crawler.fb_get_post_list(pagename, from_date, to_date) print(postList) #분석 dataString = analizer.json_to_str( "C:/Users/aran0/Desktop/BIT/python/facebook/channelanews.json", "message_str") count_data = analizer.count_wordfreq(dataString) print(count_data) dictWord = dict(count_data.most_common(20)) #그래프 visualizer.show_graph_bar(dictWord, pagename) visualizer.wordcloud(dictWord, pagename)