Splitting strings containing newline command and outputting to two columns

A minimal example of my data looks as follows:

import pandas as pd

data = {'address': ['STREET ADDRESS', 'C/O NAME LASTNAMEnOTHER STREET ADDRESS'], 'coaddress':['', '']}

df = pd.DataFrame(data)

df

I am looking for a way (using pandas, preferably) to:

1. identify rows in which the address column contains “C/O”, and
2. split the string at the newline (n) command and output the part of the string before the newline command to the corresponding row in the coaddress column and keep the part of the string after the newline command in the address column.

The df I want to achieve looks as follows:

desired_data = {'address': ['STREET ADDRESS', 'OTHER STREET ADDRESS'], 'coaddress':['', 'C/O NAME LASTNAME']}

desired_df = pd.DataFrame(desired_data)

desired_df

Any suggestions on how to achieve this? Thanks!

Answer

We can do it in full Pandas using loc, contains and split like so :

df.loc[df["address"].str.contains('C/O'), 'coaddress'] = df["address"].str.split('n').str[0]
df.loc[df["address"].str.contains('C/O'), 'address'] = df["address"].str.split('n').str[1]

Output :

    address                 coaddress
0   STREET ADDRESS  
1   OTHER STREET ADDRESS    C/O NAME LASTNAME

UPDATE :

As commented by @Neither, we can avoid some repetition by setting a function here :

def reassign(df, col, elt):
    condition = df["address"].str.contains('C/O')
    element = df["address"].str.split('n')
    df.loc[condition, col] = element.str[elt]
    return df

col_elt = {'coaddress': 0, 'address': 1}

for key in col_elt:
    df = reassign(df, key, col_elt[key])