python-3.x - 用 % 在数字上拆分 Pandas 列

Question

我有一个 df，其中一列显示如下:

**Share**
We are safe 25%
We are always safe 12.50% (India Aus, West)
We are ok (USA, EU)
We are not OK
What is this
Always wise 25.66%

我想拆分此列，以便将适用的 % 值从该列拆分为一个新的列。
所以输出将是

Share                  Percent    LOCATION
We are safe            25%  
We are always safe     12.50%     India Aus, West
We are ok                         USA, EU
We are not OK
What is this
Always wise            25.66%

我认为下面会从右边拆分它，但它不起作用

df['Percent'] = df['Share'].str.rsplit(r' \d',1).str[0]

Answer 1

您可以提取这些值:

df[['Share','Percent']] = df['Share'].str.split(r'\s+(?=\d+(?:\.\d+)?%\s*$)',expand=True).fillna("")

Pandas 测试:

import pandas as pd
df = pd.DataFrame({'Share':['We are safe 25%','We are ok', 'We are always safe 12.50%']})
df[['Share','Percent']] = df['Share'].str.split(r'\s+(?=\d+(?:\.\d+)?%\s*$)',expand=True).fillna("")
>>> df
                Share Percent
0         We are safe     25%
1           We are ok        
2  We are always safe  12.50%

见 regex demo .细节:

\s+ - 一个或多个空格

(?=\d+(?:\.\d+)?%\s*$) - 匹配一个位置的正向前瞻，紧跟其后的是:

\d+ - 一位或多位数字

(?:\.\d+)? - 可选序列 .和一位或多位数字

% - 一个 %符号

\s* - 0 个或多个尾随(如 $ 紧随其后)空格和

$ - 字符串的结尾。