如何使用正则表达式参数返回 pandas str.contains 中的匹配关键字？

Question

This is my sample code:

import pandas as pd

df = pd.DataFrame({'A':
                       ['btcrr',
                        'You have crypto here',
                        'coinbase.com was there ',
                        'hotwalletint']
                   })

regex = r"(^|\W)(?:btc|crypto|coinbase|hotwallet)[^A-Za-z0-9]"
tagged_df = df[df['A'].str.contains(regex, na=False, regex=True, case=False)]

The output of tagged_df :

   A
1  You have crypto here
2  coinbase.com was there 

In this case, this will return only if it matches the regex that I gave. But I want the pandas to return the matched keyword. I am expecting something like this to return in tagged_df

The Expected output of tagged_df :

   A
1  crypto
2  coinbase.com

If pandas do not have the ability, Please suggest alternates that can solve this case.

Answer 1

Use pandas.Series.str.extract() . For each capture group in the regular expession (a non-capture group is just a group with ?: at the beginning, eg (?:abc) ), a new colum will be created containing the matched value for that group, for that row. You can also Add ?P<your_name> to the very beginning of a capture group to name the outputted column associated with that group:

new_df = df['A'].str.extract(r'(?:^|\W)(?P<A>btc|crypto|coinbase|hotwallet)[^A-Za-z0-9]')

Output:

>>> new_df
          A
0       NaN
1    crypto
2  coinbase
3       NaN

>>> new_df.dropna()
          A
1    crypto
2  coinbase