==== extract last field from each row of a column ====
tags | pandas series str split apply if condition, string split

Given the input
<code>
 'Location': {
  0: 'San Francisco, CA, United States',
  1: 'Shanghai, China',
  2: 'Singapore'}
</code>
get something like
<code>
 'Country': {
  0: 'United States',
  1: 'China',
  2: 'Singapore'}
</code>

Solution:
<code>
In [1]: d = {'Location': {
   ...:   0: 'San Francisco, CA, United States',
   ...:   1: 'Shanghai, China',
   ...:   2: 'Singapore'}}

In [2]: import pandas as pd
   ...: df = pd.DataFrame.from_dict(d)
   ...: df
Out[2]:
                           Location
0  San Francisco, CA, United States
1                   Shanghai, China
2                         Singapore

In [3]: df['Country'] = df['Location'].str.split(',').apply(lambda x: x[-1])
   ...: df
Out[3]:
                           Location         Country
0  San Francisco, CA, United States   United States
1                   Shanghai, China           China
2                         Singapore       Singapore

In [4]: df['Country'].to_dict()
Out[4]: {0: ' United States', 1: ' China', 2: 'Singapore'}
</code>