Iterating over row and editing strings in Pandas

Good morning,

I have exhaustively searched for how best to do two things in Python/Pandas, and have not yet found the answer.

I have a df such as:

I would like iterate over the user column and leave only the text inside the parenthesis, with a result such as:

I’ve found many successful ways for iterating. I’ve not found a way to do the string edits cleanly. I’ve seen some regex suggestions but am not all that familiar with how to implement them based on the other examples given.

>Solution :

There are various ways to do that.

One way would be using pandas.Series.apply and a custom lambda function as follows

df['User'] = df['User'].apply(lambda x: x[x.find('(')+1:x.find(')')])

[Out]:

            User  Role
0    rogerdodger  user
1    edwincullen  user
2  hunterandrews  user

Another way could be with pandas.Series.str.extract as follows

df['User'] = df['User'].str.extract(r'\((.*?)\)', expand=False)

[Out]:

            User  Role
0    rogerdodger  user
1    edwincullen  user
2  hunterandrews  user

Notes:

• If needed, one can also store the username in a different column, such as the column username as follows

  df['username'] = df['User'].str.extract(r'\((.*?)\)', expand=False)
  
  [Out]:
                               User  Role       username
  0      Roger Dodger (rogerdodger)  user    rogerdodger
  1      Edwin Cullen (edwincullen)  user    edwincullen
  2  Hunter Andrews (hunterandrews)  user  hunterandrews