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)
