Replace second group of a regex match on a pandas dataframe

Question

I have a dataframe of about 1000 rows and my requirement is to replace all characters that appear after username: to a common string (say 'users').

I'm making use of the following regex that suits my problem and I can match all usernames in the second group which I want to replace with 'users'

Regex:

"(?i)(\busername\b\s?|\buname\s?)+[;|:]
(\s?[a-z-A-Z0-9@:!+=#$%^&*-]{5,})"

Test data:

 username : user111
    uname : user212

Expected Output:

username : users
uname : users

Also I wanted to do this operation on a large dataset so i'm looking if there are any efficient ways of achieving this.

Answer 1

I'm sure you could use regex for this, but sometimes the simplest thing to to is split and join such as:

df = pd.DataFrame({'values':['username : user111','uname : user212']})

df['values'].apply(lambda x: ': '.join([x.split(':')[0], 'users']))

Or if you'd like to avoid lambda:

df['values'].str.split(':').str.get(0) + ': users'

Output

             values
0  username : users
1     uname : users