这些对文本的操作经常用到， 那我就总结一下。 陆续补充。。。
操作：
strip_html(cls, text) 去除html标签
separate_words(cls, text, min_lenth=3) 文本提取
get_words_frequency(cls, words_list) 获取词频
源码：
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class DocProcess(object): @classmethod def strip_html(cls, text): """ Delete html tags in text. text is String """ new_text = " " is_html = False for character in text: if character == "<": is_html = True elif character == ">": is_html = False new_text += " " elif is_html is False: new_text += character return new_text @classmethod def separate_words(cls, text, min_lenth=3): """ Separate text into words in list. """ splitter = re.compile("\\W+") return [s.lower() for s in splitter.split(text) if len(s) > min_lenth] @classmethod def get_words_frequency(cls, words_list): """ Get frequency of words in words_list. return a dict. """ num_words = {} for word in words_list: num_words[word] = num_words.get(word, 0) + 1 return num_words |
以上这篇python 文本单词提取和词频统计的实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/autoliuweijie/article/details/50687419
