文本文件“紅樓夢. txt”中包含了《紅樓夢》小說前20章內容，“ 停用詞. txt”包含了需要排除的詞語。實現以下功能。????????????????????????????????????????????????????????????????????????????????????????????????
1.對“紅樓夢. txt”中文本進行分詞，并對人物名稱進行歸-化處理，僅歸一化以下內容:????????????????????????????????????????????????????????????????????????????????????????????????
鳳姐、鳳姐兒、鳳丫頭歸-為鳳姐
寶玉、二爺、寶二爺歸-為寶玉
黛玉、顰兒、林妹妹、黛玉道歸-為黛玉
寶釵、寶丫頭歸一為寶釵
賈母、老祖宗歸-為賈母
襲人、襲人道歸一為襲人
賈政、賈政道歸一為賈政
賈鏈、璉二爺歸一為賈璉
2.不統計“停用詞.txt"文件中包含詞語的詞頻（名字必須大于一個字）。????????????????????????????????????????????????????????????????????????????????????????????????
3.提取出場次數不少于40次的人物名稱，將人物名稱及其出場次教按照遞減排序，保存到result.csv文件中，出場次數相同的.則按照人物名稱的字符順序排序。????????????????????????????????????????????????????????????????????????????????????????????????
輸出示例????????????????????????????????????????????????????????????????????????????????????????????????
寶玉,597
鳳姐,296
一個,179
如今,132
黛玉,113
一面,112

方法1： import jieba f = "紅樓夢.txt" sf = "停用詞.txt" f1=open(f,'r',encoding='utf-8') txt=jieba.lcut(f1.read()) f2=open(sf,'r',encoding='utf-8') lines=f2.readlines() ty=[] #存放停用詞 for line in lines:ty.append(line[:-1]) #去掉行尾換行符 txt0=[] #存放剔除停用詞后的紅樓夢文本 for x in txt:if x not in ty:txt0.append(x) d={} for word in txt0:if len(word)<=1:continueelif word == '鳳姐兒' or word == '鳳丫頭':rword = '鳳姐'elif word == '二爺' or word == '寶二爺':rword = '寶玉'elif word == '顰兒' or word == '林妹妹' or word == '黛玉道':rword = '黛玉'elif word == '寶丫頭':rword = '寶釵'elif word == '老祖宗':rword = '賈母'elif word == '襲人道':rword = '襲人'elif word == '賈政道':rword = '賈政'elif word == '璉二爺':rword = '賈璉'else:rword=wordd[rword]=d.get(rword,0)+1 ls = list(d.items()) ls.sort(key=lambda x: x[1], reverse=True) fo=open(r'result.csv', 'a', encoding='utf-8') for i in ls:if i[1]>=40:print("{},{}".format(i[0],i[1]))fo.write("{},{}\n".format(i[0],i[1])) f1.close() f2.close() fo.close() 方法2： import jieba f = "紅樓夢.txt" sf = "停用詞.txt" txt = jieba.lcut(open(f, 'r', encoding='utf-8').read()) # open函數讀取紅樓夢文本并分詞 ,正式考試可以不用指定編碼，用系統默認。 f.read()讀入全部內容。jieba.lcut()返回一個列表類型的分詞結果。 stop_words = [] with open(sf, 'r', encoding='utf-8') as f: # 讀取停用詞文本并分割文本后添加到stop_words列表中。with語句打開文件，好處是讀取文件后自動關閉，不需要手動關閉。for i in f.read().splitlines(): #str.splitlines([keepends])：返回一個列表，分割符為('\r','\r\n','\n')即按行分割。默認參數keepends為False，意思是不保留每行結尾的'\n'，反之保留。stop_words.append(i) # 剔除停用詞 txt0 = [x for x in txt if x not in stop_words] # 統計詞頻 counts = {} for word in txt0:if len(word) == 1: # 跳過標點符號和字continueelif word == '鳳姐兒' or word == '鳳丫頭':rword = '鳳姐'elif word == '二爺' or word == '寶二爺':rword = '寶玉'elif word == '顰兒' or word == '林妹妹' or word == '黛玉道':rword = '黛玉'elif word == '寶丫頭':rword = '寶釵'elif word == '老祖宗':rword = '賈母'elif word == '襲人道':rword = '襲人'elif word == '賈政道':rword = '賈政'elif word == '璉二爺':rword = '賈璉'else:rword = wordcounts[rword] = counts.get(rword, 0) + 1 # 固定語句將字典的值進行排序 li = list(counts.items()) li.sort(key=lambda x: x[1], reverse=True) # 列出詞頻超過40的結果 with open('result.csv', 'a', encoding='gbk') as f:for i in li:key, value = iif value < 40:breakf.write(key + ',' + str(value) + '\n') #value為intprint(key + ',' + str(value))

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