양지수

Merge branch 'revert-07d85895' into 'master'

Revert "Merge branch 'master' into 'master'"

This reverts merge request !1

See merge request !2
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1 -import warnings
2 -#########5/23일작성중 #########
3 -warnings.simplefilter(("ignore"))
4 -import openpyxl
5 -import pandas as pd
6 -
7 -####### [날짜, 뉴스단어 한개] 구성 만드는 파일 차트 분석 시 count함수 이욜 할 때 참조 자료
8 -# ex)hmm뉴스키워드날짜뉴스모으고특수삭제.xlsx 파일 넣음<- DayNewsMerge.py 중간에 주석처리 된 부분 해제하고 결과 얻기
9 -Stockfilename = input("키워드파일이름입력:")
10 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/샘플/" + Stockfilename + ".xlsx"
11 -Stockfile = openpyxl.load_workbook(fileStock) # 파일이름입력
12 -stock_ws = Stockfile.active
13 -Stock_data = [] # list 타입
14 -date=[]
15 -i = 0
16 -for row in stock_ws.rows:
17 - Stock_data.append([])
18 - date.append(row[1].value)
19 - for cell in row:
20 - if cell.value != None :
21 - Stock_data[i].append(cell.value)
22 - i += 1
23 -del Stock_data[0]
24 -del date[0]
25 -for i in range(len(Stock_data)):
26 - del Stock_data[i][0] #각 열의 첫번째 행 삭제
27 -for i in range(len(Stock_data)):
28 - del Stock_data[i][0] #각 열의 첫번째 행 삭제
29 -print(Stock_data)
30 -print(date)
31 -a=[] #
32 -print(len(date),len(Stock_data))
33 -for j in range(len(Stock_data)):
34 - for k in range(len(Stock_data[j])):
35 - a.append([date[j],Stock_data[j][k]])
36 -print(a)
37 -df_SourTar = pd.DataFrame(a)
38 -df_SourTar.to_excel(Stockfilename+'countif.xlsx',sheet_name='sheet1')
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1 -import pandas as pd
2 -
3 -source = {
4 - '학년': [1, 2, 1, 3, 4],
5 - '성별': ['남자', '여자', '남자', '여자', '남자'],
6 - '국어': [98, 88, 92, 63, 120],
7 - '영어': [88, 90, 70, 60, 50],
8 - '수학': [64, 62, None, 31, None],
9 - '과학': [None, 72, None, 70, 88]
10 -}
11 -df = pd.DataFrame(source)
12 -df1=df[(df['성별']!='남자')].index
13 -df2=df.drop(df1)
14 -print(df)
15 -print("---------")
16 -print(df2)
1 -import warnings
2 -
3 -warnings.simplefilter(("ignore"))
4 -import openpyxl
5 -import pandas as pd
6 -
7 -# 000_KNU_New_Vdic2.xlsx 파일 넣기
8 -
9 -Stockfilefolder = input("종목시세폴더입력: ")
10 -Stockfilename = input("시세파일이름입력:")
11 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/뉴스키워드/" + Stockfilefolder + "/" + Stockfilename + ".xlsx"
12 -Stockfile = openpyxl.load_workbook(fileStock) # 파일이름입력
13 -stock_ws = Stockfile.active
14 -Stock_data = [] # list 타입
15 -i = 0
16 -for row in stock_ws.rows:
17 - Stock_data.append([])
18 - for cell in row:
19 - if cell.value != None:
20 - Stock_data[i].append(cell.value)
21 - i += 1
22 -del Stock_data[0]
23 -for i in range(len(Stock_data)):
24 - del Stock_data[i][0]
25 -#print(Stock_data)
26 -
27 -
28 -vert_p = [] # 수직 중복 삭제
29 -for i in range(len(Stock_data)):
30 - vert_p.append([])
31 - for j in range(len(Stock_data[i])):
32 - vert_p[i].append(Stock_data[i][j]) # 단어만 넣기
33 -print(vert_p)
34 -
35 -vert_p.sort(key=lambda x: x[0]) # 단어 기준으로 정렬
36 -for i in range(len(vert_p) - 2): # 단어 비교해서 같으면 누적, 다르면 값 바꾸기
37 - for j in range(i + 1, len(vert_p)):
38 - if vert_p[i][0] == vert_p[j][0] :
39 - vert_p[i][1] += vert_p[j][1]
40 - vert_p[j] = ['0', 0]
41 - if str.isalnum(vert_p[i][0]) == False:
42 - vert_p[i] =['0', 0]
43 -
44 -vert_p = [i for i in vert_p if not '0' in i] # '0'들어간 열 제거
45 -df_ver = pd.DataFrame(vert_p)
46 -df_ver.to_excel(Stockfilename + ' Stock_dictionary2.xlsx', sheet_name='sheet1')
47 -####사전 완성####
1 -import warnings
2 -
3 -warnings.simplefilter(("ignore"))
4 -import openpyxl
5 -import pandas as pd
6 -
7 -Stockfilefolder = input("종목시세폴더입력: ")
8 -Stockfilename = input("시세파일이름입력:")
9 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/종목별시세/" + Stockfilefolder + "/" + Stockfilename + ".xlsx"
10 -Stockfile = openpyxl.load_workbook(fileStock) # 파일이름입력
11 -stock_ws = Stockfile.active
12 -Stock_data = [] # list 타입
13 -i = 0
14 -for row in stock_ws.rows:
15 - Stock_data.append([])
16 - for cell in row:
17 - if cell.value != None:
18 - Stock_data[i].append(cell.value)
19 - i += 1
20 -del Stock_data[0]
21 -for i in range(len(Stock_data)):
22 - del Stock_data[i][0] # 대비 삭제
23 -#print(Stock_data)
24 -
25 -
26 -vert_p = [] # 수직 중복 삭제
27 -for i in range(len(Stock_data)):
28 - vert_p.append([])
29 - for j in range(len(Stock_data[i])):
30 - vert_p[i].append(Stock_data[i][j]) # 단어만 넣기
31 -print(vert_p)
32 -
33 -vert_p.sort(key=lambda x: x[0]) # 단어 기준으로 정렬
34 -for i in range(len(vert_p) - 2): # 단어 비교해서 같으면 누적 다르면 값 바꾸기
35 - for j in range(i + 1, len(vert_p)):
36 - if vert_p[i][0] == vert_p[j][0] :
37 - vert_p[i][1] += vert_p[j][1]
38 - vert_p[j] = ['0', 0]
39 - if str.isalnum(vert_p[i][0]) == False:
40 - vert_p[i] =['0', 0]
41 -
42 -vert_p = [i for i in vert_p if not '0' in i] # '0'들어간 열 제거
43 -df_ver = pd.DataFrame(vert_p)
44 -df_ver.to_excel(Stockfilename + ' Stock_dictionary2.xlsx', sheet_name='sheet1')
1 -# **뉴스 키워드 노출 빈도수에 따른 기업 주가 영향 분석**
2 ----------------------------------------------------
3 -----------------------------------------------------
4 -
5 -
6 -## **지도교수님**
7 -* 한치근 교수님
8 -
9 -## **팀원**
10 -* 2017104003 컴퓨터공학과 양지수
11 -* 2017104039 컴퓨터공학과 한서흔
12 -
13 ----
14 -
15 -## **개발일정**
16 -* 2021.03.09~2021.03.22 데이터 수집
17 -* 2021.03.23~2021.04.19 자연어 처리,중간보고서 작성
18 -* 2021.04.20~2021.05.04 감성사전 분석 및 특화 사전 제작
19 -* 2021.05.05~ 중심성 분석 및 최종 결과 제작
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1 -import warnings
2 -warnings.simplefilter(("ignore"))
3 -import konlpy
4 -from konlpy.tag import *
5 -import openpyxl
6 -import pandas as pd
7 -from math import log10
8 -import numpy as np
9 -
10 -#형태소분석라이브러리
11 -#okt = Okt()
12 -hannanum = Hannanum()
13 -#filename= input("분석할 파일이름 입력:") #파일명
14 -filefolder = input("종목폴더입력: ")
15 -filename=input("파일이름입력:")
16 -filepos = "C:/Users/yangj/PycharmProjects/pythonProject1/뉴스크롤링/"+filefolder+"/" + filename + ".xlsx"
17 -kfile = openpyxl.load_workbook(filepos)#파일이름입력
18 -sheet=kfile.worksheets[0]#sheet1에 있는 데이터 가죠오기
19 -#print(sheet)
20 -data=[]
21 -for row in sheet.rows: #data에 크롤링한 뉴스 제목들 저장
22 - data.append(
23 - row[1].value
24 - )
25 -#print(data)
26 -#print(type(data[1])) #str
27 -
28 -newData2=[]
29 -
30 -#print(newData)
31 -for i in range(len(data)-1):
32 - newData2.append(hannanum.nouns(data[i+1])) #명사만 추출hannanum가 okt보다 성능좋음
33 -#print(newData2)
34 -
35 -newData3=[]
36 -for i in range(len(newData2)):
37 - newData3.append([])
38 - for j in newData2[i]:
39 - if any(map(str.isdigit,j))==False and len(j)>1: #추출한 결과가 숫자포함이거나 한글자 인것 제외
40 - newData3[i].append(j)
41 -#print(newData3)
42 -
43 -#print(type(newData2))#newData2 데이터 형식은 list
44 -#df= pd.DataFrame.from_records(newData3)#newData3 dataframe으로 변환
45 -#df.to_excel(filename+'_명사추출_숫자제외'+'.xlsx') #파일명의 엑셀로 변환
46 -
47 -#TF-IDF함수 시작
48 -
49 -def f(t, d): # 엑셀 d 안에 있는 t 빈도 세기
50 - return d.count(t)
51 -
52 -def tf(t, d): #tf(t,d)증가빈도 공식 적용
53 - return 0.5 + 0.5*f(t,d)/max([f(w,d) for w in d])
54 -
55 -def idf(t, D): #역문서 빈도 공식 적용
56 - numerator = len(D) #문서 집합에 포함 된 문서 수
57 - denominator = 1 + len([ True for d in D if t in d]) #1더해서 0되는 것 방지
58 - return log10(numerator/denominator)
59 -
60 -def tfidf(t, d, D):
61 - return tf(t,d)*idf(t, D)
62 -
63 -def tfidfScorer(D):
64 - result = []
65 - for d in D:
66 - result.append([(t, tfidf(t, d, D)) for t in d] )
67 - return result
68 -
69 -#newData3는 명사추출을 통해 분리되어있음(이미 split상태)
70 -
71 -if __name__ == '__main__':
72 - corpus=[]
73 - for i in range(len(newData3)):
74 - corpus.append(newData3[i])
75 - TfIf=[] #결과저장
76 - for i, result in enumerate(tfidfScorer(corpus)):
77 - #print('====== document[%d] ======' % i)
78 - #print(result)
79 - TfIf.append(result)
80 -print(TfIf)#TFIF는 (단어,가중치) 조합으로 저장
81 -for i in range(len(TfIf)-1):
82 - TfIf[i].sort(key=lambda x:x[1], reverse=True) #가중치기준 내림차순 정렬
83 -print(TfIf)
84 -onlynouns = []
85 -for i in range(len(TfIf)):
86 - onlynouns.append([])
87 - for j in range(len(TfIf[i])):
88 - for k in range(len(TfIf[i][j])):
89 - if k%2==0:
90 - onlynouns[i].append(TfIf[i][j][k])
91 -print(onlynouns)
92 -#df= pd.DataFrame.from_records(TfIf)#TfIf dataframe으로 변환
93 -#df.to_excel(filename+'_가중치추출_내림정렬'+'.xlsx')
94 -
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460 - <env name="PYTHONUNBUFFERED" value="1" />
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...\ No newline at end of file ...\ No newline at end of file
1 -import warnings
2 -
3 -warnings.simplefilter(("ignore"))
4 -import openpyxl
5 -import pandas as pd
6 -
7 -#######Gephi에 사용할 edge파일 만들기 전에 필요한 자료 만드는 과정
8 -####6개월치 키워드 합친 키워드 파일 넣기
9 -
10 -Stockfilename = input("키워드파일이름입력:")
11 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/샘플/" + Stockfilename + ".xlsx"
12 -Stockfile = openpyxl.load_workbook(fileStock) # 파일이름입력
13 -stock_ws = Stockfile.active
14 -Stock_data = [] # list 타입
15 -date=[]
16 -i = 0
17 -for row in stock_ws.rows:
18 - Stock_data.append([])
19 - date.append(row[1].value)
20 - for cell in row:
21 - if cell.value != None:
22 - Stock_data[i].append(cell.value)
23 - i += 1
24 -del Stock_data[0] #첫번째 의미없는 열 삭제
25 -del date[0]
26 -for i in range(len(Stock_data)):
27 - del Stock_data[i][0] #각 열의 첫번째 행 삭제
28 -for i in range(len(Stock_data)):
29 - del Stock_data[i][0] #각 열의 날짜 행 삭제
30 -
31 -
32 -Tdata=[]
33 -
34 -for x in range(len(Stock_data)):
35 - Tdata.append([])
36 - for y in range(len(Stock_data[x])):
37 - if str.isalnum(Stock_data[x][y]) == True:
38 - Tdata[x].append(Stock_data[x][y])
39 -
40 -result = { '날짜':date, '단어':Tdata }
41 -
42 -df = pd.DataFrame(result)
43 -#print(df)
44 -list_df=df.values.tolist() #dataframe list로 변경
45 -print(list_df)
46 -#print(list_df[0][0]) 날짜 2021.01.01.
47 -
48 -new_date = [] # 날짜 중복 삭제
49 -for v in date:
50 - if v not in new_date:
51 - new_date.append(v)
52 -#print(new_date)
53 -
54 -Setlist =[]# 날짜별 키워드 넣기
55 -for v in range(len(new_date)):
56 - Setlist.append([])
57 - Setlist[v].append(new_date[v])
58 - for i in range(len(list_df)):
59 - for j in range(len(list_df[i][1])):
60 - if new_date[v] == list_df[i][0] :
61 - Setlist[v].append(list_df[i][1][j])
62 -print(Setlist)
63 -df_ver= pd.DataFrame(Setlist)
64 -#df_ver.to_excel(Stockfilename+' 날짜뉴스모으고특수삭제.xlsx',sheet_name='sheet1')
65 -SourceTarget=[]
66 -for i in range(len(list_df)):
67 - SourceTarget.append([])
68 - for j in range(len(list_df[i][1])-1):
69 - SourceTarget.append([list_df[i][0],list_df[i][1][j],list_df[i][1][j+1],1])
70 -print(SourceTarget)
71 -SourceTarget = [v for v in SourceTarget if v]
72 -df_SourTar = pd.DataFrame(SourceTarget)
73 -df_SourTar.to_excel(Stockfilename+'Edge3.xlsx',sheet_name='sheet1')
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1 -# KNU 한국어 감성사전
2 -# 작성자 : 온병원, 박상민, 나철원
3 -# 소속 : 군산대학교 소프트웨어융합공학과 Data Intelligence Lab
4 -# 홈페이지 : dilab.kunsan.ac.kr
5 -# 작성일 : 2018.05.14
6 -# 뜻풀이 데이터 출처 : https://github.com/mrchypark/stdkor
7 -# 신조어 데이터 출처 : https://ko.wikipedia.org/wiki/%EB%8C%80%ED%95%9C%EB%AF%BC%EA%B5%AD%EC%9D%98_%EC%9D%B8%ED%84%B0%EB%84%B7_%EC%8B%A0%EC%A1%B0%EC%96%B4_%EB%AA%A9%EB%A1%9D
8 -# 이모티콘 데이터 출처: https://ko.wikipedia.org/wiki/%EC%9D%B4%EB%AA%A8%ED%8B%B0%EC%BD%98
9 -# SentiWordNet_3.0.0_20130122 데이터 출처 : http://sentiwordnet.isti.cnr.it/
10 -# SenticNet-5.0 데이터 출처 : http://sentic.net/
11 -# 감정단어사전0603 데이터 출처 : http://datascience.khu.ac.kr/board/bbs/board.php?bo_table=05_01&wr_id=91
12 -# 김은영, “국어 감정동사 연구”, 2004.02, 학위논문(박사) - 전남대학교 국어국문학과 대학원
13 -
14 -#-*-coding:utf-8-*-
15 -import collections
16 -import json
17 -
18 -import warnings
19 -warnings.simplefilter(("ignore"))
20 -import openpyxl
21 -import pandas as pd
22 -import re
23 -from datetime import datetime
24 -
25 -############종목 감성 판단 ex)hmm뉴스키워드.xlsx 파일 넣는 과정
26 -class KnuSL():
27 -
28 - def data_list(wordname):
29 - with open('KnuSentiLex/data/SentiWord_info.json', encoding='utf-8-sig', mode='r') as f:
30 - data = json.load(f)
31 - result = [0,0]
32 -
33 - for i in range(0, len(data)):
34 - if data[i]['word'] == wordname:
35 - result.pop()
36 - result.pop()
37 - result.append(data[i]['word_root'])
38 - result.append(int(data[i]['polarity']))
39 -
40 - r_word = result[0] #어근
41 - s_word = result[1] #극성
42 -
43 - return s_word
44 -
45 -if __name__ == "__main__":
46 -
47 - ksl = KnuSL
48 -
49 - print("\nKNU 한국어 감성사전입니다~ :)")
50 - print("사전에 단어가 없는 경우 결과가 None으로 나타납니다!!!")
51 - print("종료하시려면 #을 입력해주세요!!!")
52 - print("-2:매우 부정, -1:부정, 0:중립 or Unkwon, 1:긍정, 2:매우 긍정")
53 - print("\n")
54 -#########
55 -Newsfilefolder = input("종목폴더입력: ")
56 -Newsfilename=input("파일이름입력:")
57 -Newsfilepos = "C:/Users/yangj/PycharmProjects/pythonProject1/뉴스키워드/"+Newsfilefolder+"/" + Newsfilename + ".xlsx"
58 -Newsfile = openpyxl.load_workbook(Newsfilepos)#파일이름입력
59 -ws=Newsfile.active
60 -data=[]
61 -date=[]
62 -i=0
63 -for row in ws.rows:
64 - data.append([])
65 - date.append(row[1].value)
66 - for cell in row:
67 - if cell.value != None:
68 - data[i].append(cell.value)
69 - i += 1
70 -del data[0] #첫번째 의미없는 열 삭제
71 -del date[0]
72 -for i in range(len(data)):
73 - del data[i][0] #각 열의 첫번째 행 삭제
74 -for i in range(len(data)):
75 - del data[i][0] #각 열의 날짜 행 삭제
76 -
77 -KNUdata=[]
78 -Tdata=[]
79 -
80 -for x in range(len(data)):
81 - KNUdata.append([])
82 - Tdata.append([])
83 - for y in range(len(data[x])):
84 - KNUdata[x].append(ksl.data_list(data[x][y]))
85 - Tdata[x].append([data[x][y], KNUdata[x][y]])
86 -
87 -result = { '날짜':date, '단어, 극성':Tdata }
88 -
89 -df = pd.DataFrame(result)
90 -#print(df)
91 -list_df=df.values.tolist() #dataframe list로 변경
92 -#print(list_df)
93 -#print(list_df[0][0]) 날짜 2021.01.01.
94 -
95 -new_date = [] # 날짜 중복 삭제
96 -for v in date:
97 - if v not in new_date:
98 - new_date.append(v)
99 -#print(new_date)
100 -
101 -Setlist =[]# 날짜별 키워드 넣기
102 -for v in range(len(new_date)):
103 - Setlist.append([])
104 - Setlist[v].append(new_date[v])
105 - for i in range(len(list_df)):
106 - for j in range(len(list_df[i][1])):
107 - if new_date[v] == list_df[i][0]:
108 - Setlist[v].append(list_df[i][1][j])
109 -print(Setlist)
110 -print(Setlist[0][0]) #2021.01.01
111 -print(type(Setlist[0][0]))
112 -print(Setlist[0][0].split('-'))
113 -print(Setlist[0][1][1]) #극성 0
114 -print(type(Setlist[0][1][1])) #극성 모든 타입 int
115 -
116 -#print(list_df[0][1][0]) 키워드와 극성 ['HMM…"체질개선해', 'X']
117 -#print(list_df[0][1][0][1]) 극성 x
118 -#print(list_df[0][0].split('.')[:3]) ['2021', '01', '01']
119 -#df.to_excel(Newsfilename+' KNU.xlsx',sheet_name='sheet1')
120 -
121 -Stockfilefolder = input("종목시세폴더입력: ")
122 -Stockfilename=input("시세파일이름입력:")
123 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/종목별시세/"+Stockfilefolder+"/" + Stockfilename + ".xlsx"
124 -Stockfile = openpyxl.load_workbook(fileStock)#파일이름입력
125 -stock_ws=Stockfile.active
126 -Stock_data=[] #list 타입
127 -i=0
128 -for row in stock_ws.rows:
129 - Stock_data.append([])
130 - for cell in row:
131 - if cell.value != None:
132 - Stock_data[i].append(cell.value)
133 - i += 1
134 -del Stock_data[0]
135 -for i in range(len(Stock_data)):
136 - del Stock_data[i][2] # 대비 삭제
137 -for i in range(len(Stock_data)):
138 - del Stock_data[i][7] #거래대금 삭제
139 -for i in range(len(Stock_data)):
140 - del Stock_data[i][7] #시가 총액 삭제
141 -for i in range(len(Stock_data)):
142 - del Stock_data[i][7] #상장주식 수 삭제 / 결과:'일자', '종가', '등락률', '시가', '고가', '저가', '거래량'
143 -#print(Stock_data)
144 -
145 -def Calpercentage(a,b): #시초가 대비 고점/저점 비율
146 - return abs(a-b)/a*100
147 -####아래로 수정 필요 (미완성)####
148 -
149 -i=0
150 -for k in range(len(Setlist)):
151 - if( Stock_data[i][0].split('/') == Setlist[k][0].split('-')): # 날짜 비교 날짜가 같다면
152 - if Calpercentage(Stock_data[i][3],Stock_data[i][4]) > 2 : #당일 시가 대비 고가가 2퍼 높을때
153 - for j in range(1,len(Setlist[k])):
154 - if Setlist[k][j][1] == 0:
155 - Setlist[k][j][1] = 1
156 - else:
157 - Setlist[0][j][1] += 1
158 - elif Calpercentage(Stock_data[i][3],Stock_data[i][5]) < -2 : #당일 시가 대비 저가가 2퍼 낮을 때
159 - for j in range(1,len(Setlist[k])):
160 - if Setlist[k][j][1] == 0:
161 - Setlist[k][j][1] = -1
162 - else:
163 - Setlist[0][j][1] -= 1
164 - else:
165 - if Stock_data[i+1][2] > 0: # 다음날 주가 등락률이 양수면
166 - for j in range(1,len(Setlist[k])): #어제뉴스는 호재 취급
167 - if Setlist[k][j][1] == 0:
168 - Setlist[k][j][1] = 1
169 - else:
170 - Setlist[k][j][1] += 1
171 - elif Stock_data[i+1][2] < 0:
172 - for j in range(1,len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
173 - if Setlist[k][j][1] == 0:
174 - Setlist[k][j][1] = -1
175 - else:
176 - Setlist[k][j][1] -= 1
177 - i+=1
178 - else:
179 - if Calpercentage(Stock_data[i][3], Stock_data[i][4]) > 2: # 당일 시가 대비 고가가 2퍼 높을때
180 - for j in range(1, len(Setlist[k])):
181 - if Setlist[k][j][1] == 0:
182 - Setlist[k][j][1] = 1
183 - else:
184 - Setlist[k][j][1] += 1
185 - elif Calpercentage(Stock_data[i][3], Stock_data[i][5]) < -2: # 당일 시가 대비 저가가 2퍼 낮을 때
186 - for j in range(1, len(Setlist[k])):
187 - if Setlist[k][j][1] == 0:
188 - Setlist[k][j][1] = -1
189 - else:
190 - Setlist[k][j][1] -= 1
191 - else:
192 - if Stock_data[i + 1][2] > 0: # 다음날 주가 등락률이 양수면
193 - for j in range(1, len(Setlist[k])): # 어제뉴스는 호재 취급
194 - if Setlist[k][j][1] == 0:
195 - Setlist[k][j][1] = 1
196 - else:
197 - Setlist[k][j][1] += 1
198 - elif Stock_data[i + 1][2] < 0:
199 - for j in range(1, len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
200 - if Setlist[k][j][1] == 0:
201 - Setlist[k][j][1] = -1
202 - else:
203 - Setlist[k][j][1] -= 1
204 - i+=1 #<이거 삭제서 hmm한번 더 돌려보기
205 -
206 -print(Setlist)
207 -
208 -#df_Setlist = pd.DataFrame(Setlist)
209 -#df_Setlist.to_excel(Stockfilename+' KNU_New.xlsx',sheet_name='sheet1')
210 -
211 -Setlist_w = []
212 -for i in range(len(Setlist)):
213 - Setlist_w.append([])
214 - for j in range(1, len(Setlist[i])):
215 - Setlist_w[i].append(Setlist[i][j][0]) # 극성 제외 단어만 추출
216 -
217 -counter = {}
218 -for i in range(len(Setlist_w)):
219 - counter[i] = collections.Counter(Setlist_w[i]) # 누적치
220 -
221 -for i in range(len(Setlist_w)):
222 - Setlist_w[i] = list(zip(counter[i].keys(), counter[i].values())) # 튜플 리스트화 [(값, 값)]
223 -
224 -Plist = []
225 -for i in range(len(Setlist_w)):
226 - Plist.append([])
227 - for j in range(len(Setlist_w[i])):
228 - Plist[i].append(list(Setlist_w[i][j])) # 튜플 -> 리스트화 [[값, 값]]
229 -
230 -for i in range(len(Plist)):
231 - for j in range(len(Plist[i])):
232 - Plist[i][j][1] = 0 # 극성 0으로 초기화
233 -
234 -for i in range(len(Setlist)):
235 - for j in range(1, len(Setlist[i])):
236 - for h in range(len(Plist[i])):
237 - if Setlist[i][j][0] == Plist[i][h][0]:
238 - Plist[i][h][1] += Setlist[i][j][1] #누적치
239 -vert_p=[] #수직 중복 삭제
240 -for i in range(len(Plist)):
241 - for j in range(len(Plist[i])):
242 - vert_p.append(Plist[i][j]) #단어만 넣기
243 -#print(vert_p)
244 -vert_p.sort(key=lambda x:x[0]) #단어 기준으로 정렬
245 -for i in range(len(vert_p)-2): #단어 비교해서 같으면 누적 다르면 값 바꾸기
246 - for j in range(i+1,len(vert_p)):
247 - if vert_p[i][0] == vert_p[j][0]:
248 - vert_p[i][1]+=vert_p[j][1]
249 - vert_p[j]=['0',0]
250 -print(vert_p)
251 -vert_p=[i for i in vert_p if not '0' in i] #'0'들어간 열 제거
252 -df_ver= pd.DataFrame(vert_p)
253 -df_ver.to_excel(Stockfilename+' KNU_New_Vdic2.xlsx',sheet_name='sheet1')
254 -
255 -####키워드파일 월별로 돌려서 그 나온 결과 파일들을 합쳐서 Merge_dictionay.py에 넣어서 사전 만들기 ####
256 -
257 -
1 -# KNU 한국어 감성사전
2 -# 작성자 : 온병원, 박상민, 나철원
3 -# 소속 : 군산대학교 소프트웨어융합공학과 Data Intelligence Lab
4 -# 홈페이지 : dilab.kunsan.ac.kr
5 -# 작성일 : 2018.05.14
6 -# 뜻풀이 데이터 출처 : https://github.com/mrchypark/stdkor
7 -# 신조어 데이터 출처 : https://ko.wikipedia.org/wiki/%EB%8C%80%ED%95%9C%EB%AF%BC%EA%B5%AD%EC%9D%98_%EC%9D%B8%ED%84%B0%EB%84%B7_%EC%8B%A0%EC%A1%B0%EC%96%B4_%EB%AA%A9%EB%A1%9D
8 -# 이모티콘 데이터 출처: https://ko.wikipedia.org/wiki/%EC%9D%B4%EB%AA%A8%ED%8B%B0%EC%BD%98
9 -# SentiWordNet_3.0.0_20130122 데이터 출처 : http://sentiwordnet.isti.cnr.it/
10 -# SenticNet-5.0 데이터 출처 : http://sentic.net/
11 -# 감정단어사전0603 데이터 출처 : http://datascience.khu.ac.kr/board/bbs/board.php?bo_table=05_01&wr_id=91
12 -# 김은영, “국어 감정동사 연구”, 2004.02, 학위논문(박사) - 전남대학교 국어국문학과 대학원
13 -
14 -#-*-coding:utf-8-*-
15 -import collections
16 -import json
17 -
18 -import warnings
19 -warnings.simplefilter(("ignore"))
20 -import openpyxl
21 -import pandas as pd
22 -import re
23 -from datetime import datetime
24 -
25 -class KnuSL():
26 -
27 - def data_list(wordname):
28 - with open('KnuSentiLex/data/SentiWord_info.json', encoding='utf-8-sig', mode='r') as f:
29 - data = json.load(f)
30 - result = [0,0]
31 -
32 - for i in range(0, len(data)):
33 - if data[i]['word'] == wordname:
34 - result.pop()
35 - result.pop()
36 - result.append(data[i]['word_root'])
37 - result.append(int(data[i]['polarity']))
38 -
39 - r_word = result[0] #어근
40 - s_word = result[1] #극성
41 -
42 - return s_word
43 -
44 -if __name__ == "__main__":
45 -
46 - ksl = KnuSL
47 -
48 - print("\nKNU 한국어 감성사전입니다~ :)")
49 - print("사전에 단어가 없는 경우 결과가 None으로 나타납니다!!!")
50 - print("종료하시려면 #을 입력해주세요!!!")
51 - print("-2:매우 부정, -1:부정, 0:중립 or Unkwon, 1:긍정, 2:매우 긍정")
52 - print("\n")
53 -#########
54 -Newsfilefolder = input("종목폴더입력: ")
55 -Newsfilename=input("파일이름입력:")
56 -Newsfilepos = "C:/Users/yangj/PycharmProjects/pythonProject1/뉴스키워드/"+Newsfilefolder+"/" + Newsfilename + ".xlsx"
57 -Newsfile = openpyxl.load_workbook(Newsfilepos)#파일이름입력
58 -ws=Newsfile.active
59 -data=[]
60 -date=[]
61 -i=0
62 -for row in ws.rows:
63 - data.append([])
64 - date.append(row[1].value)
65 - for cell in row:
66 - if cell.value != None:
67 - data[i].append(cell.value)
68 - i += 1
69 -del data[0] #첫번째 의미없는 열 삭제
70 -del date[0]
71 -for i in range(len(data)):
72 - del data[i][0] #각 열의 첫번째 행 삭제
73 -for i in range(len(data)):
74 - del data[i][0] #각 열의 날짜 행 삭제
75 -
76 -KNUdata=[]
77 -Tdata=[]
78 -
79 -for x in range(len(data)):
80 - KNUdata.append([])
81 - Tdata.append([])
82 - for y in range(len(data[x])):
83 - KNUdata[x].append(ksl.data_list(data[x][y]))
84 - Tdata[x].append([data[x][y], KNUdata[x][y]])
85 -
86 -result = { '날짜':date, '단어, 극성':Tdata }
87 -
88 -df = pd.DataFrame(result)
89 -#print(df)
90 -list_df=df.values.tolist() #dataframe list로 변경
91 -#print(list_df)
92 -#print(list_df[0][0]) 날짜 2021.01.01.
93 -
94 -new_date = [] # 날짜 중복 삭제
95 -for v in date:
96 - if v not in new_date:
97 - new_date.append(v)
98 -#print(new_date)
99 -
100 -Setlist =[]# 날짜별 키워드 넣기
101 -for v in range(len(new_date)):
102 - Setlist.append([])
103 - Setlist[v].append(new_date[v])
104 - for i in range(len(list_df)):
105 - for j in range(len(list_df[i][1])):
106 - if new_date[v] == list_df[i][0]:
107 - Setlist[v].append(list_df[i][1][j])
108 -#print(Setlist)
109 -#print(Setlist[0][0]) #2021.01.01
110 -#print(Setlist[0][1][1]) #극성 0
111 -#print(type(Setlist[0][1][1])) #극성 모든 타입 int
112 -
113 -#print(list_df[0][1][0]) 키워드와 극성 ['HMM…"체질개선해', 'X']
114 -#print(list_df[0][1][0][1]) 극성 x
115 -#print(list_df[0][0].split('.')[:3]) ['2021', '01', '01']
116 -#df.to_excel(Newsfilename+' KNU.xlsx',sheet_name='sheet1')
117 -
118 -Stockfilefolder = input("종목시세폴더입력: ")
119 -Stockfilename=input("시세파일이름입력:")
120 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/종목별시세/"+Stockfilefolder+"/" + Stockfilename + ".xlsx"
121 -Stockfile = openpyxl.load_workbook(fileStock)#파일이름입력
122 -stock_ws=Stockfile.active
123 -Stock_data=[] #list 타입
124 -i=0
125 -for row in stock_ws.rows:
126 - Stock_data.append([])
127 - for cell in row:
128 - if cell.value != None:
129 - Stock_data[i].append(cell.value)
130 - i += 1
131 -del Stock_data[0]
132 -for i in range(len(Stock_data)):
133 - del Stock_data[i][2] # 대비 삭제
134 -for i in range(len(Stock_data)):
135 - del Stock_data[i][7] #거래대금 삭제
136 -for i in range(len(Stock_data)):
137 - del Stock_data[i][7] #시가 총액 삭제
138 -for i in range(len(Stock_data)):
139 - del Stock_data[i][7] #상장주식 수 삭제 / 결과:'일자', '종가', '등락률', '시가', '고가', '저가', '거래량'
140 -#print(Stock_data)
141 -
142 -def Calpercentage(a,b): #시초가 대비 고점/저점 비율
143 - return abs(a-b)/a*100
144 -####아래로 수정 필요 (미완성)####
145 -
146 -i=0
147 -for k in range(len(Setlist)):
148 - if( Stock_data[i][0].split('/') == Setlist[k][0].split('.')[:3]): # 날짜 비교 날짜가 같다면
149 - if Calpercentage(Stock_data[i][3],Stock_data[i][4]) > 2 : #당일 시가 대비 고가가 2퍼 높을때
150 - for j in range(1,len(Setlist[k])):
151 - if Setlist[k][j][1] == 0:
152 - Setlist[k][j][1] = 1
153 - else:
154 - Setlist[0][j][1] += 1
155 - elif Calpercentage(Stock_data[i][3],Stock_data[i][5]) < -2 : #당일 시가 대비 저가가 2퍼 낮을 때
156 - for j in range(1,len(Setlist[k])):
157 - if Setlist[k][j][1] == 0:
158 - Setlist[k][j][1] = -1
159 - else:
160 - Setlist[0][j][1] -= 1
161 - else:
162 - if Stock_data[i+1][2] > 0: # 다음날 주가 등락률이 양수면
163 - for j in range(1,len(Setlist[k])): #어제뉴스는 호재 취급
164 - if Setlist[k][j][1] == 0:
165 - Setlist[k][j][1] = 1
166 - else:
167 - Setlist[k][j][1] += 1
168 - elif Stock_data[i+1][2] < 0:
169 - for j in range(1,len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
170 - if Setlist[k][j][1] == 0:
171 - Setlist[k][j][1] = -1
172 - else:
173 - Setlist[k][j][1] -= 1
174 - i+=1
175 - else:
176 - if Calpercentage(Stock_data[i][3], Stock_data[i][4]) > 2: # 당일 시가 대비 고가가 2퍼 높을때
177 - for j in range(1, len(Setlist[k])):
178 - if Setlist[k][j][1] == 0:
179 - Setlist[k][j][1] = 1
180 - else:
181 - Setlist[k][j][1] += 1
182 - elif Calpercentage(Stock_data[i][3], Stock_data[i][5]) < -2: # 당일 시가 대비 저가가 2퍼 낮을 때
183 - for j in range(1, len(Setlist[k])):
184 - if Setlist[k][j][1] == 0:
185 - Setlist[k][j][1] = -1
186 - else:
187 - Setlist[k][j][1] -= 1
188 - else:
189 - if Stock_data[i + 1][2] > 0: # 다음날 주가 등락률이 양수면
190 - for j in range(1, len(Setlist[k])): # 어제뉴스는 호재 취급
191 - if Setlist[k][j][1] == 0:
192 - Setlist[k][j][1] = 1
193 - else:
194 - Setlist[k][j][1] += 1
195 - elif Stock_data[i + 1][2] < 0:
196 - for j in range(1, len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
197 - if Setlist[k][j][1] == 0:
198 - Setlist[k][j][1] = -1
199 - else:
200 - Setlist[k][j][1] -= 1
201 - i+=1
202 -
203 -print(Setlist)
204 -'''
205 -Stock_dic=[]
206 -
207 -for i in range(len(Setlist)):
208 - Stock_dic.append([])
209 - j = 2
210 - for k in range(1,len(Setlist[i])-1):
211 - if Setlist[i][k][0]== Setlist[i][j][0]:
212 - Setlist[i][k][1]+=Setlist[i][j][1]
213 - Stock_dic.append(Setlist[i][k])
214 - j+=1
215 - else:
216 - Stock_dic.append(Setlist[i][k])
217 - j+=1
218 -print(Stock_dic)
219 -'''
220 -
221 -#df_Setlist = pd.DataFrame(Setlist)
222 -#df_Setlist.to_excel(Stockfilename+' KNU_New.xlsx',sheet_name='sheet1')
223 -
224 -Setlist_w = []
225 -for i in range(len(Setlist)):
226 - Setlist_w.append([])
227 - for j in range(1, len(Setlist[i])):
228 - Setlist_w[i].append(Setlist[i][j][0]) # 극성 제외 단어만 추출
229 -
230 -counter = {}
231 -for i in range(len(Setlist_w)):
232 - counter[i] = collections.Counter(Setlist_w[i]) # 누적치
233 -
234 -for i in range(len(Setlist_w)):
235 - Setlist_w[i] = list(zip(counter[i].keys(), counter[i].values())) # 튜플 리스트화 [(값, 값)]
236 -
237 -Plist = []
238 -for i in range(len(Setlist_w)):
239 - Plist.append([])
240 - for j in range(len(Setlist_w[i])):
241 - Plist[i].append(list(Setlist_w[i][j])) # 튜플 -> 리스트화 [[값, 값]]
242 -
243 -for i in range(len(Plist)):
244 - for j in range(len(Plist[i])):
245 - Plist[i][j][1] = 0 # 극성 0으로 초기화
246 -
247 -for i in range(len(Setlist)):
248 - for j in range(1, len(Setlist[i])):
249 - for h in range(len(Plist[i])):
250 - if Setlist[i][j][0] == Plist[i][h][0]:
251 - Plist[i][h][1] += Setlist[i][j][1] #누적치
252 -vert_p=[] #수직 중복 삭제
253 -for i in range(len(Plist)):
254 - for j in range(len(Plist[i])):
255 - vert_p.append(Plist[i][j]) #단어만 넣기
256 -#print(vert_p)
257 -vert_p.sort(key=lambda x:x[0]) #단어 기준으로 정렬
258 -for i in range(len(vert_p)-2): #단어 비교해서 같으면 누적 다르면 값 바꾸기
259 - for j in range(i+1,len(vert_p)):
260 - if vert_p[i][0] == vert_p[j][0]:
261 - vert_p[i][1]+=vert_p[j][1]
262 - vert_p[j]=['0',0]
263 -print(vert_p)
264 -vert_p=[i for i in vert_p if not '0' in i] #'0'들어간 열 제거
265 -df_ver= pd.DataFrame(vert_p)
266 -df_ver.to_excel(Stockfilename+' KNU_New_vdic2.xlsx',sheet_name='sheet1')
267 -
268 -#p_result = {'날짜': new_date, '단어, 극성': Plist}
269 -#print(p_result)
270 -#df_p_result = pd.DataFrame(p_result)
271 -#df_p_result.to_excel(Stockfilename+' KNU_New_dic.xlsx',sheet_name='sheet1')
272 -'''
273 -for i in range(len(Stock_data)-1):
274 - for k in range(len(Setlist)):
275 - if (Stock_data[i][0].split('/') == Setlist[k][0].split('.')[:3]): # 날짜 비교
276 - if Calpercentage(Stock_data[i][3], Stock_data[i][4]) > 2 : #당일 시가 대비 고가가 2퍼 높을때
277 - for j in range(1, len(Setlist[k])):
278 - if Setlist[k][j][1] == 0:
279 - Setlist[k][j][1] = 1
280 - else:
281 - Setlist[k][j][1] += 1
282 - elif Calpercentage(Stock_data[i][3], Stock_data[i][5]) < -2 : #당일 시가 대비 저가가 2퍼 낮을 때
283 - for j in range(1, len(Setlist[k])):
284 - if Setlist[k][j][1] == 0:
285 - Setlist[k][j][1] = -1
286 - else:
287 - Setlist[k][j][1] -= 1
288 - else:
289 - if Stock_data[i+1][2] > 0: # 다음날 주가 등락률이 양수면
290 - for j in range(1, len(Setlist[k])): #어제뉴스는 호재 취급
291 - if Calpercentage(Stock_data[i+1][3], Stock_data[i+1][5]) < -2 :
292 - for j in range(1, len(Setlist[k])):
293 - if Setlist[k][j][1] == 0:
294 - Setlist[k][j][1] = -1
295 - else:
296 - Setlist[k][j][1] -= 1
297 - else:
298 - if Setlist[k][j][1] == 0:
299 - Setlist[k][j][1] = 1
300 - else:
301 - Setlist[k][j][1] += 1
302 - elif Stock_data[i+1][2] < 0:
303 - if Calpercentage(Stock_data[i+1][3], Stock_data[i+1][4]) > 2 :
304 - for j in range(1, len(Setlist[k])):
305 - if Setlist[k][j][1] == 0:
306 - Setlist[k][j][1] = 1
307 - else:
308 - Setlist[k][j][1] += 1
309 - else:
310 - for j in range(1, len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
311 - if Setlist[k][j][1] == 0:
312 - Setlist[k][j][1] = -1
313 - else:
314 - Setlist[k][j][1] -= -1
315 - else:
316 -
317 -
318 -print(Setlist)
319 -
320 -'''
1 -# -*-coding:utf-8-*-
2 -import collections
3 -import json
4 -
5 -import warnings
6 -
7 -warnings.simplefilter(("ignore"))
8 -import openpyxl
9 -import pandas as pd
10 -import re
11 -from datetime import datetime
12 -
13 -########코스피 감성 판단
14 -class KnuSL():
15 -
16 - def data_list(wordname):
17 - with open('KnuSentiLex/data/SentiWord_info.json', encoding='utf-8-sig', mode='r') as f:
18 - data = json.load(f)
19 - result = [0, 0]
20 -
21 - for i in range(0, len(data)):
22 - if data[i]['word'] == wordname:
23 - result.pop()
24 - result.pop()
25 - result.append(data[i]['word_root'])
26 - result.append(int(data[i]['polarity']))
27 -
28 - r_word = result[0] # 어근
29 - s_word = result[1] # 극성
30 -
31 - return s_word
32 -
33 -
34 -if __name__ == "__main__":
35 - ksl = KnuSL
36 -
37 - print("\nKNU 한국어 감성사전입니다~ :)")
38 - print("사전에 단어가 없는 경우 결과가 None으로 나타납니다!!!")
39 - print("종료하시려면 #을 입력해주세요!!!")
40 - print("-2:매우 부정, -1:부정, 0:중립 or Unkwon, 1:긍정, 2:매우 긍정")
41 - print("\n")
42 -#########
43 -Newsfilefolder = input("종목폴더입력: ")
44 -Newsfilename = input("파일이름입력:")
45 -Newsfilepos = "C:/Users/yangj/PycharmProjects/pythonProject1/뉴스키워드/" + Newsfilefolder + "/" + Newsfilename + ".xlsx"
46 -Newsfile = openpyxl.load_workbook(Newsfilepos) # 파일이름입력
47 -ws = Newsfile.active
48 -data = []
49 -date = []
50 -i = 0
51 -for row in ws.rows:
52 - data.append([])
53 - date.append(row[1].value)
54 - for cell in row:
55 - if cell.value != None:
56 - data[i].append(cell.value)
57 - i += 1
58 -del data[0] # 첫번째 의미없는 열 삭제
59 -del date[0]
60 -for i in range(len(data)):
61 - del data[i][0] # 각 열의 첫번째 행 삭제
62 -for i in range(len(data)):
63 - del data[i][0] # 각 열의 날짜 행 삭제
64 -
65 -KNUdata = []
66 -Tdata = []
67 -
68 -for x in range(len(data)):
69 - KNUdata.append([])
70 - Tdata.append([])
71 - for y in range(len(data[x])):
72 - KNUdata[x].append(ksl.data_list(data[x][y]))
73 - Tdata[x].append([data[x][y], KNUdata[x][y]])
74 -
75 -result = {'날짜': date, '단어, 극성': Tdata}
76 -
77 -df = pd.DataFrame(result)
78 -
79 -list_df = df.values.tolist() # dataframe list로 변경
80 -new_date = [] # 날짜 중복 삭제
81 -for v in date:
82 - if v not in new_date:
83 - new_date.append(v)
84 -# print(new_date)
85 -
86 -Setlist = [] # 날짜별 키워드 넣기
87 -for v in range(len(new_date)):
88 - Setlist.append([])
89 - Setlist[v].append(new_date[v])
90 - for i in range(len(list_df)):
91 - for j in range(len(list_df[i][1])):
92 - if new_date[v] == list_df[i][0]:
93 - Setlist[v].append(list_df[i][1][j])
94 -
95 -Stockfilefolder = input("종목시세폴더입력: ")
96 -Stockfilename = input("시세파일이름입력:")
97 -fileStock = "C:/Users/yangj/PycharmProjects/pythonProject1/종목별시세/" + Stockfilefolder + "/" + Stockfilename + ".xlsx"
98 -Stockfile = openpyxl.load_workbook(fileStock) # 파일이름입력
99 -stock_ws = Stockfile.active
100 -Stock_data = [] # list 타입
101 -i = 0
102 -for row in stock_ws.rows:
103 - Stock_data.append([])
104 - for cell in row:
105 - if cell.value != None:
106 - Stock_data[i].append(cell.value)
107 - i += 1
108 -del Stock_data[0]
109 -for i in range(len(Stock_data)):
110 - del Stock_data[i][2] # 대비 삭제
111 -for i in range(len(Stock_data)):
112 - del Stock_data[i][7] # 거래대금 삭제
113 -for i in range(len(Stock_data)):
114 - del Stock_data[i][7] # 시가 총액 삭제
115 -
116 -
117 -i = 0
118 -for k in range(len(Setlist)):
119 - if (Stock_data[i][0].split('/') == Setlist[k][0].split('.')[:3]): # 날짜 비교 날짜가 같다면
120 - if Stock_data[i][2] > 0: # 코스피 등락이 양수
121 - for j in range(1, len(Setlist[k])):
122 - if Setlist[k][j][1] == 0:
123 - Setlist[k][j][1] = 1
124 - else:
125 - Setlist[k][j][1] += 1
126 - elif Stock_data[i][2] < 0:
127 - for j in range(1, len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
128 - if Setlist[k][j][1] == 0:
129 - Setlist[k][j][1] = -1
130 - else:
131 - Setlist[k][j][1] -= 1
132 - i += 1
133 - else:
134 - if Stock_data[i+1][2] > 0: # 다음날 주가 등락률이 양수면
135 - for j in range(1, len(Setlist[k])): # 어제뉴스는 호재 취급
136 - if Setlist[k][j][1] == 0:
137 - Setlist[k][j][1] = 1
138 - else:
139 - Setlist[k][j][1] += 1
140 - elif Stock_data[i+1][2] < 0:
141 - for j in range(1, len(Setlist[k])): # 음수면 어제 뉴스는 악재 취급
142 - if Setlist[k][j][1] == 0:
143 - Setlist[k][j][1] = -1
144 - else:
145 - Setlist[k][j][1] -= 1
146 -
147 -Setlist_w = []
148 -for i in range(len(Setlist)):
149 - Setlist_w.append([])
150 - for j in range(1, len(Setlist[i])):
151 - Setlist_w[i].append(Setlist[i][j][0]) # 극성 제외 단어만 추출
152 -
153 -counter = {}
154 -for i in range(len(Setlist_w)):
155 - counter[i] = collections.Counter(Setlist_w[i]) # 누적치
156 -
157 -for i in range(len(Setlist_w)):
158 - Setlist_w[i] = list(zip(counter[i].keys(), counter[i].values())) # 튜플 리스트화 [(값, 값)]
159 -
160 -Plist = []
161 -for i in range(len(Setlist_w)):
162 - Plist.append([])
163 - for j in range(len(Setlist_w[i])):
164 - Plist[i].append(list(Setlist_w[i][j])) # 튜플 -> 리스트화 [[값, 값]]
165 -
166 -for i in range(len(Plist)):
167 - for j in range(len(Plist[i])):
168 - Plist[i][j][1] = 0 # 극성 0으로 초기화
169 -
170 -for i in range(len(Setlist)):
171 - for j in range(1, len(Setlist[i])):
172 - for h in range(len(Plist[i])):
173 - if Setlist[i][j][0] == Plist[i][h][0]:
174 - Plist[i][h][1] += Setlist[i][j][1] # 누적치
175 -vert_p = [] # 수직 중복 삭제
176 -for i in range(len(Plist)):
177 - for j in range(len(Plist[i])):
178 - vert_p.append(Plist[i][j]) # 단어만 넣기
179 -# print(vert_p)
180 -vert_p.sort(key=lambda x: x[0]) # 단어 기준으로 정렬
181 -for i in range(len(vert_p) - 2): # 단어 비교해서 같으면 누적 다르면 값 바꾸기
182 - for j in range(i + 1, len(vert_p)):
183 - if vert_p[i][0] == vert_p[j][0]:
184 - vert_p[i][1] += vert_p[j][1]
185 - vert_p[j] = ['0', 0]
186 -
187 -vert_p = [i for i in vert_p if not '0' in i] # '0'들어간 열 제거
188 -df_ver = pd.DataFrame(vert_p)
189 -df_ver.to_excel(Stockfilename + ' KNU_New_vdic2.xlsx', sheet_name='sheet1')
1 -# This file was automatically generated by SWIG (http://www.swig.org).
2 -# Version 3.0.0
3 -#
4 -# Do not make changes to this file unless you know what you are doing--modify
5 -# the SWIG interface file instead.
6 -
7 -
8 -
9 -
10 -
11 -from sys import version_info
12 -if version_info >= (2,6,0):
13 - def swig_import_helper():
14 - from os.path import dirname
15 - import imp
16 - fp = None
17 - try:
18 - fp, pathname, description = imp.find_module('_MeCab', [dirname(__file__)])
19 - except ImportError:
20 - import _MeCab
21 - return _MeCab
22 - if fp is not None:
23 - try:
24 - _mod = imp.load_module('_MeCab', fp, pathname, description)
25 - finally:
26 - fp.close()
27 - return _mod
28 - _MeCab = swig_import_helper()
29 - del swig_import_helper
30 -else:
31 - import _MeCab
32 -del version_info
33 -try:
34 - _swig_property = property
35 -except NameError:
36 - pass # Python < 2.2 doesn't have 'property'.
37 -def _swig_setattr_nondynamic(self,class_type,name,value,static=1):
38 - if (name == "thisown"): return self.this.own(value)
39 - if (name == "this"):
40 - if type(value).__name__ == 'SwigPyObject':
41 - self.__dict__[name] = value
42 - return
43 - method = class_type.__swig_setmethods__.get(name,None)
44 - if method: return method(self,value)
45 - if (not static):
46 - self.__dict__[name] = value
47 - else:
48 - raise AttributeError("You cannot add attributes to %s" % self)
49 -
50 -def _swig_setattr(self,class_type,name,value):
51 - return _swig_setattr_nondynamic(self,class_type,name,value,0)
52 -
53 -def _swig_getattr(self,class_type,name):
54 - if (name == "thisown"): return self.this.own()
55 - method = class_type.__swig_getmethods__.get(name,None)
56 - if method: return method(self)
57 - raise AttributeError(name)
58 -
59 -def _swig_repr(self):
60 - try: strthis = "proxy of " + self.this.__repr__()
61 - except: strthis = ""
62 - return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
63 -
64 -try:
65 - _object = object
66 - _newclass = 1
67 -except AttributeError:
68 - class _object : pass
69 - _newclass = 0
70 -
71 -
72 -class DictionaryInfo(_object):
73 - __swig_setmethods__ = {}
74 - __setattr__ = lambda self, name, value: _swig_setattr(self, DictionaryInfo, name, value)
75 - __swig_getmethods__ = {}
76 - __getattr__ = lambda self, name: _swig_getattr(self, DictionaryInfo, name)
77 - __repr__ = _swig_repr
78 - __swig_getmethods__["filename"] = _MeCab.DictionaryInfo_filename_get
79 - if _newclass:filename = _swig_property(_MeCab.DictionaryInfo_filename_get)
80 - __swig_getmethods__["charset"] = _MeCab.DictionaryInfo_charset_get
81 - if _newclass:charset = _swig_property(_MeCab.DictionaryInfo_charset_get)
82 - __swig_getmethods__["size"] = _MeCab.DictionaryInfo_size_get
83 - if _newclass:size = _swig_property(_MeCab.DictionaryInfo_size_get)
84 - __swig_getmethods__["type"] = _MeCab.DictionaryInfo_type_get
85 - if _newclass:type = _swig_property(_MeCab.DictionaryInfo_type_get)
86 - __swig_getmethods__["lsize"] = _MeCab.DictionaryInfo_lsize_get
87 - if _newclass:lsize = _swig_property(_MeCab.DictionaryInfo_lsize_get)
88 - __swig_getmethods__["rsize"] = _MeCab.DictionaryInfo_rsize_get
89 - if _newclass:rsize = _swig_property(_MeCab.DictionaryInfo_rsize_get)
90 - __swig_getmethods__["version"] = _MeCab.DictionaryInfo_version_get
91 - if _newclass:version = _swig_property(_MeCab.DictionaryInfo_version_get)
92 - __swig_getmethods__["next"] = _MeCab.DictionaryInfo_next_get
93 - if _newclass:next = _swig_property(_MeCab.DictionaryInfo_next_get)
94 - def __init__(self):
95 - this = _MeCab.new_DictionaryInfo()
96 - try: self.this.append(this)
97 - except: self.this = this
98 - __swig_destroy__ = _MeCab.delete_DictionaryInfo
99 - __del__ = lambda self : None;
100 -DictionaryInfo_swigregister = _MeCab.DictionaryInfo_swigregister
101 -DictionaryInfo_swigregister(DictionaryInfo)
102 -
103 -class Path(_object):
104 - __swig_setmethods__ = {}
105 - __setattr__ = lambda self, name, value: _swig_setattr(self, Path, name, value)
106 - __swig_getmethods__ = {}
107 - __getattr__ = lambda self, name: _swig_getattr(self, Path, name)
108 - def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined")
109 - __repr__ = _swig_repr
110 - __swig_getmethods__["rnode"] = _MeCab.Path_rnode_get
111 - if _newclass:rnode = _swig_property(_MeCab.Path_rnode_get)
112 - __swig_getmethods__["rnext"] = _MeCab.Path_rnext_get
113 - if _newclass:rnext = _swig_property(_MeCab.Path_rnext_get)
114 - __swig_getmethods__["lnode"] = _MeCab.Path_lnode_get
115 - if _newclass:lnode = _swig_property(_MeCab.Path_lnode_get)
116 - __swig_getmethods__["lnext"] = _MeCab.Path_lnext_get
117 - if _newclass:lnext = _swig_property(_MeCab.Path_lnext_get)
118 - __swig_getmethods__["cost"] = _MeCab.Path_cost_get
119 - if _newclass:cost = _swig_property(_MeCab.Path_cost_get)
120 - __swig_setmethods__["prob"] = _MeCab.Path_prob_set
121 - __swig_getmethods__["prob"] = _MeCab.Path_prob_get
122 - if _newclass:prob = _swig_property(_MeCab.Path_prob_get, _MeCab.Path_prob_set)
123 -Path_swigregister = _MeCab.Path_swigregister
124 -Path_swigregister(Path)
125 -
126 -class Node(_object):
127 - __swig_setmethods__ = {}
128 - __setattr__ = lambda self, name, value: _swig_setattr(self, Node, name, value)
129 - __swig_getmethods__ = {}
130 - __getattr__ = lambda self, name: _swig_getattr(self, Node, name)
131 - def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined")
132 - __repr__ = _swig_repr
133 - __swig_getmethods__["prev"] = _MeCab.Node_prev_get
134 - if _newclass:prev = _swig_property(_MeCab.Node_prev_get)
135 - __swig_getmethods__["next"] = _MeCab.Node_next_get
136 - if _newclass:next = _swig_property(_MeCab.Node_next_get)
137 - __swig_getmethods__["enext"] = _MeCab.Node_enext_get
138 - if _newclass:enext = _swig_property(_MeCab.Node_enext_get)
139 - __swig_getmethods__["bnext"] = _MeCab.Node_bnext_get
140 - if _newclass:bnext = _swig_property(_MeCab.Node_bnext_get)
141 - __swig_getmethods__["rpath"] = _MeCab.Node_rpath_get
142 - if _newclass:rpath = _swig_property(_MeCab.Node_rpath_get)
143 - __swig_getmethods__["lpath"] = _MeCab.Node_lpath_get
144 - if _newclass:lpath = _swig_property(_MeCab.Node_lpath_get)
145 - __swig_getmethods__["feature"] = _MeCab.Node_feature_get
146 - if _newclass:feature = _swig_property(_MeCab.Node_feature_get)
147 - __swig_getmethods__["id"] = _MeCab.Node_id_get
148 - if _newclass:id = _swig_property(_MeCab.Node_id_get)
149 - __swig_getmethods__["length"] = _MeCab.Node_length_get
150 - if _newclass:length = _swig_property(_MeCab.Node_length_get)
151 - __swig_getmethods__["rlength"] = _MeCab.Node_rlength_get
152 - if _newclass:rlength = _swig_property(_MeCab.Node_rlength_get)
153 - __swig_getmethods__["rcAttr"] = _MeCab.Node_rcAttr_get
154 - if _newclass:rcAttr = _swig_property(_MeCab.Node_rcAttr_get)
155 - __swig_getmethods__["lcAttr"] = _MeCab.Node_lcAttr_get
156 - if _newclass:lcAttr = _swig_property(_MeCab.Node_lcAttr_get)
157 - __swig_getmethods__["posid"] = _MeCab.Node_posid_get
158 - if _newclass:posid = _swig_property(_MeCab.Node_posid_get)
159 - __swig_getmethods__["char_type"] = _MeCab.Node_char_type_get
160 - if _newclass:char_type = _swig_property(_MeCab.Node_char_type_get)
161 - __swig_getmethods__["stat"] = _MeCab.Node_stat_get
162 - if _newclass:stat = _swig_property(_MeCab.Node_stat_get)
163 - __swig_getmethods__["isbest"] = _MeCab.Node_isbest_get
164 - if _newclass:isbest = _swig_property(_MeCab.Node_isbest_get)
165 - __swig_getmethods__["alpha"] = _MeCab.Node_alpha_get
166 - if _newclass:alpha = _swig_property(_MeCab.Node_alpha_get)
167 - __swig_getmethods__["beta"] = _MeCab.Node_beta_get
168 - if _newclass:beta = _swig_property(_MeCab.Node_beta_get)
169 - __swig_setmethods__["prob"] = _MeCab.Node_prob_set
170 - __swig_getmethods__["prob"] = _MeCab.Node_prob_get
171 - if _newclass:prob = _swig_property(_MeCab.Node_prob_get, _MeCab.Node_prob_set)
172 - __swig_getmethods__["wcost"] = _MeCab.Node_wcost_get
173 - if _newclass:wcost = _swig_property(_MeCab.Node_wcost_get)
174 - __swig_getmethods__["cost"] = _MeCab.Node_cost_get
175 - if _newclass:cost = _swig_property(_MeCab.Node_cost_get)
176 - __swig_getmethods__["surface"] = _MeCab.Node_surface_get
177 - if _newclass:surface = _swig_property(_MeCab.Node_surface_get)
178 -Node_swigregister = _MeCab.Node_swigregister
179 -Node_swigregister(Node)
180 -
181 -MECAB_NOR_NODE = _MeCab.MECAB_NOR_NODE
182 -MECAB_UNK_NODE = _MeCab.MECAB_UNK_NODE
183 -MECAB_BOS_NODE = _MeCab.MECAB_BOS_NODE
184 -MECAB_EOS_NODE = _MeCab.MECAB_EOS_NODE
185 -MECAB_EON_NODE = _MeCab.MECAB_EON_NODE
186 -MECAB_SYS_DIC = _MeCab.MECAB_SYS_DIC
187 -MECAB_USR_DIC = _MeCab.MECAB_USR_DIC
188 -MECAB_UNK_DIC = _MeCab.MECAB_UNK_DIC
189 -MECAB_ONE_BEST = _MeCab.MECAB_ONE_BEST
190 -MECAB_NBEST = _MeCab.MECAB_NBEST
191 -MECAB_PARTIAL = _MeCab.MECAB_PARTIAL
192 -MECAB_MARGINAL_PROB = _MeCab.MECAB_MARGINAL_PROB
193 -MECAB_ALTERNATIVE = _MeCab.MECAB_ALTERNATIVE
194 -MECAB_ALL_MORPHS = _MeCab.MECAB_ALL_MORPHS
195 -MECAB_ALLOCATE_SENTENCE = _MeCab.MECAB_ALLOCATE_SENTENCE
196 -MECAB_ANY_BOUNDARY = _MeCab.MECAB_ANY_BOUNDARY
197 -MECAB_TOKEN_BOUNDARY = _MeCab.MECAB_TOKEN_BOUNDARY
198 -MECAB_INSIDE_TOKEN = _MeCab.MECAB_INSIDE_TOKEN
199 -class Lattice(_object):
200 - __swig_setmethods__ = {}
201 - __setattr__ = lambda self, name, value: _swig_setattr(self, Lattice, name, value)
202 - __swig_getmethods__ = {}
203 - __getattr__ = lambda self, name: _swig_getattr(self, Lattice, name)
204 - __repr__ = _swig_repr
205 - def clear(self): return _MeCab.Lattice_clear(self)
206 - def is_available(self): return _MeCab.Lattice_is_available(self)
207 - def bos_node(self): return _MeCab.Lattice_bos_node(self)
208 - def eos_node(self): return _MeCab.Lattice_eos_node(self)
209 - def end_nodes(self, *args): return _MeCab.Lattice_end_nodes(self, *args)
210 - def begin_nodes(self, *args): return _MeCab.Lattice_begin_nodes(self, *args)
211 - def sentence(self): return _MeCab.Lattice_sentence(self)
212 - def size(self): return _MeCab.Lattice_size(self)
213 - def set_Z(self, *args): return _MeCab.Lattice_set_Z(self, *args)
214 - def Z(self): return _MeCab.Lattice_Z(self)
215 - def set_theta(self, *args): return _MeCab.Lattice_set_theta(self, *args)
216 - def theta(self): return _MeCab.Lattice_theta(self)
217 - def next(self): return _MeCab.Lattice_next(self)
218 - def request_type(self): return _MeCab.Lattice_request_type(self)
219 - def has_request_type(self, *args): return _MeCab.Lattice_has_request_type(self, *args)
220 - def set_request_type(self, *args): return _MeCab.Lattice_set_request_type(self, *args)
221 - def add_request_type(self, *args): return _MeCab.Lattice_add_request_type(self, *args)
222 - def remove_request_type(self, *args): return _MeCab.Lattice_remove_request_type(self, *args)
223 - def newNode(self): return _MeCab.Lattice_newNode(self)
224 - def toString(self, *args): return _MeCab.Lattice_toString(self, *args)
225 - def enumNBestAsString(self, *args): return _MeCab.Lattice_enumNBestAsString(self, *args)
226 - def has_constraint(self): return _MeCab.Lattice_has_constraint(self)
227 - def boundary_constraint(self, *args): return _MeCab.Lattice_boundary_constraint(self, *args)
228 - def feature_constraint(self, *args): return _MeCab.Lattice_feature_constraint(self, *args)
229 - def set_boundary_constraint(self, *args): return _MeCab.Lattice_set_boundary_constraint(self, *args)
230 - def set_feature_constraint(self, *args): return _MeCab.Lattice_set_feature_constraint(self, *args)
231 - def set_result(self, *args): return _MeCab.Lattice_set_result(self, *args)
232 - def what(self): return _MeCab.Lattice_what(self)
233 - def set_what(self, *args): return _MeCab.Lattice_set_what(self, *args)
234 - __swig_destroy__ = _MeCab.delete_Lattice
235 - __del__ = lambda self : None;
236 - def __init__(self):
237 - this = _MeCab.new_Lattice()
238 - try: self.this.append(this)
239 - except: self.this = this
240 - def set_sentence(self, *args): return _MeCab.Lattice_set_sentence(self, *args)
241 -Lattice_swigregister = _MeCab.Lattice_swigregister
242 -Lattice_swigregister(Lattice)
243 -
244 -class Model(_object):
245 - __swig_setmethods__ = {}
246 - __setattr__ = lambda self, name, value: _swig_setattr(self, Model, name, value)
247 - __swig_getmethods__ = {}
248 - __getattr__ = lambda self, name: _swig_getattr(self, Model, name)
249 - __repr__ = _swig_repr
250 - def dictionary_info(self): return _MeCab.Model_dictionary_info(self)
251 - def transition_cost(self, *args): return _MeCab.Model_transition_cost(self, *args)
252 - def lookup(self, *args): return _MeCab.Model_lookup(self, *args)
253 - def createTagger(self): return _MeCab.Model_createTagger(self)
254 - def createLattice(self): return _MeCab.Model_createLattice(self)
255 - def swap(self, *args): return _MeCab.Model_swap(self, *args)
256 - __swig_getmethods__["version"] = lambda x: _MeCab.Model_version
257 - if _newclass:version = staticmethod(_MeCab.Model_version)
258 - __swig_destroy__ = _MeCab.delete_Model
259 - __del__ = lambda self : None;
260 - __swig_getmethods__["create"] = lambda x: _MeCab.Model_create
261 - if _newclass:create = staticmethod(_MeCab.Model_create)
262 - def __init__(self, *args):
263 - this = _MeCab.new_Model(*args)
264 - try: self.this.append(this)
265 - except: self.this = this
266 -Model_swigregister = _MeCab.Model_swigregister
267 -Model_swigregister(Model)
268 -
269 -def Model_version():
270 - return _MeCab.Model_version()
271 -Model_version = _MeCab.Model_version
272 -
273 -def Model_create(*args):
274 - return _MeCab.Model_create(*args)
275 -Model_create = _MeCab.Model_create
276 -
277 -class Tagger(_object):
278 - __swig_setmethods__ = {}
279 - __setattr__ = lambda self, name, value: _swig_setattr(self, Tagger, name, value)
280 - __swig_getmethods__ = {}
281 - __getattr__ = lambda self, name: _swig_getattr(self, Tagger, name)
282 - __repr__ = _swig_repr
283 - def parse(self, *args): return _MeCab.Tagger_parse(self, *args)
284 - def parseToNode(self, *args): return _MeCab.Tagger_parseToNode(self, *args)
285 - def parseNBest(self, *args): return _MeCab.Tagger_parseNBest(self, *args)
286 - def parseNBestInit(self, *args): return _MeCab.Tagger_parseNBestInit(self, *args)
287 - def nextNode(self): return _MeCab.Tagger_nextNode(self)
288 - def next(self): return _MeCab.Tagger_next(self)
289 - def formatNode(self, *args): return _MeCab.Tagger_formatNode(self, *args)
290 - def set_request_type(self, *args): return _MeCab.Tagger_set_request_type(self, *args)
291 - def request_type(self): return _MeCab.Tagger_request_type(self)
292 - def partial(self): return _MeCab.Tagger_partial(self)
293 - def set_partial(self, *args): return _MeCab.Tagger_set_partial(self, *args)
294 - def lattice_level(self): return _MeCab.Tagger_lattice_level(self)
295 - def set_lattice_level(self, *args): return _MeCab.Tagger_set_lattice_level(self, *args)
296 - def all_morphs(self): return _MeCab.Tagger_all_morphs(self)
297 - def set_all_morphs(self, *args): return _MeCab.Tagger_set_all_morphs(self, *args)
298 - def set_theta(self, *args): return _MeCab.Tagger_set_theta(self, *args)
299 - def theta(self): return _MeCab.Tagger_theta(self)
300 - def dictionary_info(self): return _MeCab.Tagger_dictionary_info(self)
301 - def what(self): return _MeCab.Tagger_what(self)
302 - __swig_destroy__ = _MeCab.delete_Tagger
303 - __del__ = lambda self : None;
304 - __swig_getmethods__["create"] = lambda x: _MeCab.Tagger_create
305 - if _newclass:create = staticmethod(_MeCab.Tagger_create)
306 - __swig_getmethods__["version"] = lambda x: _MeCab.Tagger_version
307 - if _newclass:version = staticmethod(_MeCab.Tagger_version)
308 - def __init__(self, *args):
309 - this = _MeCab.new_Tagger(*args)
310 - try: self.this.append(this)
311 - except: self.this = this
312 - def parseToString(self, *args): return _MeCab.Tagger_parseToString(self, *args)
313 -Tagger_swigregister = _MeCab.Tagger_swigregister
314 -Tagger_swigregister(Tagger)
315 -
316 -def Tagger_create(*args):
317 - return _MeCab.Tagger_create(*args)
318 -Tagger_create = _MeCab.Tagger_create
319 -
320 -def Tagger_version():
321 - return _MeCab.Tagger_version()
322 -Tagger_version = _MeCab.Tagger_version
323 -
324 -VERSION = _MeCab.VERSION
325 -# This file is compatible with both classic and new-style classes.
326 -
327 -
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1 -Metadata-Version: 2.1
2 -Name: mecab-python
3 -Version: 0.996-ko-0.9.2-msvc
4 -Summary: UNKNOWN
5 -Home-page: UNKNOWN
6 -Author: UNKNOWN
7 -Author-email: UNKNOWN
8 -License: UNKNOWN
9 -Platform: UNKNOWN
10 -
11 -UNKNOWN
12 -
13 -
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1 -Wheel-Version: 1.0
2 -Generator: bdist_wheel (0.31.1)
3 -Root-Is-Purelib: false
4 -Tag: cp37-cp37m-win_amd64
5 -
1 -{"archive_info": {}, "url": "file:///C:/Users/yangj/PycharmProjects/pythonProject1/mecab_python-0.996_ko_0.9.2_msvc-cp37-cp37m-win_amd64.whl"}
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