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脚本之家。
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