如何在特定字符之前从字符串中删除特殊字符？

Question

I have a df that has a column called EMAIL , which contains various email addresses. I want to remove all the special characters, specifically., -, and _ that come before @ and append a new column NEW_EMAIL . For example, if df['EMAIL'] = 'ab_cd_123@email.com' , I want df['NEW_EMAIL'] = 'abcd123@email.com' .

I was able to remove periods successfully with my codes below, but cannot seem to remove underscore or dash in the same line of code. Right now, I am repeating the same line of codes to remove those three special characters, which is quite ugly. Can someone lend me a hand please? Thank you for your help in advance.

df['NEW_EMAIL'] = df.EMAIL.str.replace(r'\.(?!.{1,4}$)','', regex = True)
df['NEW_EMAIL'] = df.NEW_EMAIL.str.replace(r'\.(?!.{1,4}$)','', regex = True)
df['NEW_EMAIL'] = df.NEW_EMAIL.str.replace(r'\.(?!.{1,4}$)','', regex = True)

Answer 1

You can use

df['NEW_EMAIL'] = df['EMAIL'].str.replace(r'[._-](?=[^@]*@)', '', regex=True)

See the regex demo . Details :

• [._-] - a . , _ or - char
• (?=[^@]*@) - a positive lookahead that requires the presence of any zero or more chars other than @ and then a @ char immediately to the right of the current location.

If you need to replace/remove any special char , you should use

df['NEW_EMAIL'] = df['EMAIL'].str.replace(r'[\W_](?=[^@]*@)', '', regex=True)

See a Pandas test:

>>> import pandas as pd
>>> df = pd.DataFrame({'EMAIL':['ab_cd_123@email.com', 'ab_cd.12-3@email.com']})
>>> df['EMAIL'].str.replace(r'[._-](?=[^@]*@)', '', regex=True)
0    abcd123@email.com
1    abcd123@email.com
Name: EMAIL, dtype: object