如何通过正则表达式过滤 pandas 中的行 [英] How to filter rows in pandas by regex

问题描述

我想在其中一列上使用regex干净地过滤数据框.

I would like to cleanly filter a dataframe using regex on one of the columns.

举一个人为的例子:

In [210]: foo = pd.DataFrame({'a' : [1,2,3,4], 'b' : ['hi', 'foo', 'fat', 'cat']})
In [211]: foo
Out[211]: 
   a    b
0  1   hi
1  2  foo
2  3  fat
3  4  cat

我想使用正则表达式将行过滤为以f开头的行.首先去:

I want to filter the rows to those that start with f using a regex. First go:

In [213]: foo.b.str.match('f.*')
Out[213]: 
0    []
1    ()
2    ()
3    []

这不是太有用了.但是，这将使我得到我的布尔值索引:

That's not too terribly useful. However this will get me my boolean index:

In [226]: foo.b.str.match('(f.*)').str.len() > 0
Out[226]: 
0    False
1     True
2     True
3    False
Name: b

然后我可以通过以下方式进行限制:

So I could then do my restriction by:

In [229]: foo[foo.b.str.match('(f.*)').str.len() > 0]
Out[229]: 
   a    b
1  2  foo
2  3  fat

虽然这使我人为地将一个组放入正则表达式中，但似乎不是一种干净的方法.有更好的方法吗?

That makes me artificially put a group into the regex though, and seems like maybe not the clean way to go. Is there a better way to do this?

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