move string starting with specific characters into another column in pandas df - pandas

Question

I have a dataframe containing addresses.
Addressess
10 Pentland Drive, Comiston, Edinburgh, EH10 6PX.
Moray Place, Edinburgh, EH3
Carlton Street, Edinburgh
The Bourse Apartments, 47 Timber Bush, Leith EH6 6QH
I wish to write code in python and pandas that identifies if there is an 'EH' in the row and then moves this and all subsequent characters into another column. Thus achieving this:
Addressess
Post Code
10 Pentland Drive, Comiston, Edinburgh, .
EH10 6PX
Moray Place, Edinburgh,
EH3
Carlton Street, Edinburgh
The Bourse Apartments, 47 Timber Bush, Leith EH6 6QH
EH6 6QH
can anyone help?

Answer 1

You can use str.extract:
df[['Addressess', 'Post Code']] = df['Addressess'].str.extract(r'(.*?)\s*(\bEH\d+[\s\w]*)?\W*$')
regex demo
Or str.split, if there is at least one row with a post code:
df[['Addressess', 'Post Code']] = df['Addressess'].str.split(r'\s*(?=\bEH\d*)', n=1, expand=True)
regex demo
Output:
Addressess Post Code
0 10 Pentland Drive, Comiston, Edinburgh, EH10 6PX
1 Moray Place, Edinburgh, EH3
2 Carlton Street, Edinburgh NaN
3 The Bourse Apartments, 47 Timber Bush, Leith EH6 6QH

Answer 2

With simple regex matching:
df['Post Code'] = df['Addressess'].str.extract('(EH.+)').fillna('')
Addressess Post Code
0 10 Pentland Drive, Comiston, Edinburgh, EH10 6PX. EH10 6PX.
1 Moray Place, Edinburgh, EH3 EH3
2 Carlton Street, Edinburgh
3 The Bourse Apartments, 47 Timber Bush, Leith E... EH6 6QH

Answer 3

Here is a way using a regex positive lookahead:
df['Addressess'].str.split(r'[0-9A-Za-z,] (?=EH)',expand=True).rename({0:'Addressess',1:'Post Code'},axis=1)