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
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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