If you have a DataFrame containing addresses, and you want to split the addresses using Python, here is one way to do it:

Name Sex Education address Age Score dates
0 John M Bachelor 123 Main St, San Francisco, CA 94102 37 99 2023-09-05 11:43:01
1 Jane F Master 456 Elm St, New York, NY 10001 30 83 2023-09-03 00:46:36
2 Bob M PhD 789 Oak St, Los Angeles, CA 90001 25 84 2023-09-18 05:10:26
3 Emily F Bachelor 101 Pine Ave, Chicago, IL 60611 28 77 2023-09-06 20:18:57
4 Mike M High School 202 Cedar Rd, Houston, TX 77002 36 97 2023-09-04 00:29:09 
import pandas as pd

data['city'] = data['address'].apply(lambda x: x.split(',')[1])

# function way
def get_city(address):
  return address.split(',')[1]

def get_state(address):
  return address.split(',')[2].split(' ')[1]

data['city_short'] = data['address'].apply(lambda x: get_city(x)+' '+ get_state(x))

data.head()
Name Sex Education address Age Score dates city city_short
0 John M Bachelor 123 Main St, San Francisco, CA 94102 37 99 2023-09-05 11:43:01 San Francisco San Francisco CA
1 Jane F Master 456 Elm St, New York, NY 10001 30 83 2023-09-03 00:46:36 New York New York NY
2 Bob M PhD 789 Oak St, Los Angeles, CA 90001 25 84 2023-09-18 05:10:26 Los Angeles Los Angeles CA
3 Emily F Bachelor 101 Pine Ave, Chicago, IL 60611 28 77 2023-09-06 20:18:57 Chicago Chicago IL
4 Mike M High School 202 Cedar Rd, Houston, TX 77002 36 97 2023-09-04 00:29:09 Houston Houston TX