Keep original string values after pandas.series.str.extract() if the regex doesn't match

I am trying to extract emails from strings, and want to make sure that if the original value is formatted how I expect already, that it is not changed to Nan and instead is kept as is.

Example input

<class 'pandas.core.series.Series'>
1    <doe.b.john@gmail.com>
2    <doe.c.jane@gmail.com>
3    person.anonymous@hotmail.com
4    dent.arthur@space.com

I am using

# curr_emails is <class 'pandas.core.series.Series'>
curr_emails = curr_emails.str.extract(r"<([^<>]+)>").squeeze()` # regex extracts text between < >

I receive back

1    doe.b.john@gmail.com
2    doe.c.jane@gmail.com
3    NaN
4    Nan

But I instead would like

1    doe.b.john@gmail.com
2    doe.c.jane@gmail.com
3    person.anonymous@hotmail.com
4    dent.arthur@space.com

A similar question is posted here, but I could not seem to make it work with my current approach.

If there is no <> pattern, you can fill them by the original value. Or if the <> is at the beginning and the end of email, you can just strip them

curr_emails = (curr_emails.str.extract(r"<([^<>]+)>").squeeze()
               .fillna(curr_emails))
# or
curr_emails = curr_emails.str.strip(r'<>')

Try using str.replace instead of str.extract to replace < at the start of a string or > at the end of a string with ''

curr_emails.str.replace('^<|>$', '', regex=True)

0            doe.b.john@gmail.com
1            doe.c.jane@gmail.com
2    person.anonymous@hotmail.com
3           dent.arthur@space.com