DDR爱好者之家 Design By 杰米

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:

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。

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DDR爱好者之家 Design By 杰米