Python英文文章词频统计(14份剑桥真题词频统计)

 import jieba # 以只读方式打开text（即真题库） text = open('text.txt', 'r', encoding = 'utf-8').read() # len(text) #统一为小写 text = text.lower() # 需要剔除的词汇列表，也可以用记事本的形式，添加一个打开记事本的语句即可 # 即 stwlist = [line.strip() for line in open 'stopwords.txt',encoding='utf-8').readlines()] # 这里使用列表 stwlist = ['the','a','of','to','end','in','you','is','that','for','on','it','as','your','...','14', 'this','or','20','40','27','30','13','21','26','10','15','22', '32','31','1','2','4','5','6','7','8','9','0','10','11','12','13', '12','13','15','16','17','25','33','35','36','18','23','19','24', '38','29','34','37','000','...............................'] # 先进行分词 words = jieba.cut(text, cut_all = False, HMM = True) #cut_all:是否采用全模式 #HMM：是否采用HMM模型 word_ = {} for word in words: if (word.strip() not in stwlist): if len(word) > 1: if word != '\t': if word != '\r\n': # 计算词频 if word in word_: word_[word] += 1 else: word_[word] = 1 # 将结果保存为元组 word_freq = [] for word, freq in word_.items(): word_freq.append((word, freq)) # 降序排列 word_freq.sort(key = lambda x:x[1], reverse = True) #输出前3500个词汇 for i in range(3500): word, freq = word_freq[i] print('{0:10}{1:5}'.format(word, freq))