通过剥离列名来重命名列的正则表达式

Question

我的 df 有很多列，每列都有重复的值，因为它的调查数据。例如，我的数据如下所示：

df:

 Q36r9: sales platforms - Before purchasing a new car         Q36r32: Advertising letters - Before purchasing a new car
        Not Selected                                                                         Selected

所以我想从列名中删除文本。例如，我想从第一列获取“：”和“-”之间的文本。所以它应该是这样的：“销售平台”，在第二部分我想转换列的值，“选择”应该用列的名称和“未选择”更改为 NaN

所以想要的输出应该是这样的：

sales platforms                                       Advertising letters
      NaN                                             Advertising letters

已编辑：如果我的列名如下：

Q40r1c3: WeChat - Looking for a new car - And now if you think again  - Which social media platforms or sources would you use in each situation?

如果我只想在“：”和“-”之间找到一些东西。它应该提取“微信”

Answer 1

IIUC，

我们可以利用.* 的一些正则表达式和贪婪匹配，它匹配定义的模式之间的所有内容

import re

df.columns = [re.search(':(.*)-',i).group(1) for i in df.columns.str.strip()]

print(df.columns)

   sales platforms   Advertising letters 
0      Not Selected                  None

编辑：

通过贪心匹配我们可以使用+?

+? Quantifier — Matches between one and unlimited times, as few times as possible, expanding as needed (lazy)

---

Q36r9: sales platforms - Before purchasing a new car    Q40r1c3: WeChat - Looking for a new car - And now if you think again - Which social media platforms or sources would you use in each situation?
0                                                       1


import re

[re.search(':(.+?)-',i).group(1).strip() for i in df.columns]

['sales platforms', 'WeChat']