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Python文本分析
book

Python文本分析

by Jens Albrecht, Sidharth Ramachandran, Christian Winkler
August 2022
Intermediate to advanced
441 pages
11h 26m
Chinese
China Electric Power Press Ltd.
Content preview from Python文本分析
准备统计和机器学习的文本数据
111
有关元字符(比如“
^
”)以及特殊字符类(比如“
\w
”)的介绍,请参
W3Schools
https://oreil.ly/pZgG1
)。还有一些交互式的网站可供开发
和测试正则表达式,例如
https://regex101.com
(请确保将“Flavor”设置成
Python)。
在许多软件包中,你都可以找到预编译的正则表达式,类似下面这个:
RE_BRACKET = re.compile('\[[^\[\]]*\]')
text = RE_BRACKET.sub(' ', text)
预编译最初是一种提高性能的机制,但是现代 Python 可以自动缓存编译后的
正则表达式。然而,对于常见的正则表达式,使用预编译仍然有很多好处,而
且还可以提高可读性。
看一看
Reddit
数据集中的如下文本示例:
text = """
After viewing the [PINKIEPOOL Trailer](https://www.youtu.be/watch?v=ieHRoHUg)
it got me thinking about the best match ups.
<lb>Here's my take:<lb><lb>[](/sp)[](/ppseesyou) Deadpool<lb>[](/sp)[](/ajsly)
Captain America<lb>"""
如果对上述文本进行清理和打磨,那么我们肯定能获得更好的分析结果。有些标签
只是网页抓取的产物,所以我们应该剔除它们。而且我们对 ...
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Publisher Resources

ISBN: 9787519864446