$ ipython
Python 3.6.8 |Anaconda custom (64-bit)| (default, Feb 21 2019, 18:30:04) [MSC v.1916 64 bit (AMD64)]
Type 'copyright', 'credits' or 'license' for more information
IPython 7.5.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: d = {'Location': {0: 'Warszawa, Poland',
...: 1: 'San Francisco, CA, United States',
...: 2: 'Los Angeles, CA, United States',
...: 3: 'Sunnyvale, CA, United States',
...: 4: 'Sunnyvale, CA, United States',
...: 5: 'San Francisco, CA, United States',
...: 6: 'Sunnyvale, CA, United States',
...: 7: 'Kraków, Poland',
...: 8: 'Shanghai, China',
...: 9: 'Mountain View, CA, United States',
...: 10: 'Boulder, CO, United States',
...: 11: 'Boulder, CO, United States',
...: 12: 'Xinyi District, Taiwan',
...: 13: 'Tel Aviv-Yafo, Israel',
...: 14: 'Wrocław, Poland',
...: 15: 'Singapore'}}
In [2]: import pandas as pd
...: df = pd.DataFrame.from_dict(d)
...: df
Out[2]:
Location
0 Warszawa, Poland
1 San Francisco, CA, United States
2 Los Angeles, CA, United States
3 Sunnyvale, CA, United States
4 Sunnyvale, CA, United States
5 San Francisco, CA, United States
6 Sunnyvale, CA, United States
7 Kraków, Poland
8 Shanghai, China
9 Mountain View, CA, United States
10 Boulder, CO, United States
11 Boulder, CO, United States
12 Xinyi District, Taiwan
13 Tel Aviv-Yafo, Israel
14 Wrocław, Poland
15 Singapore
In [3]: df['Country'] = df['Location'].str.split(',').apply(lambda x: x[-1])
...: df
Out[3]:
Location Country
0 Warszawa, Poland Poland
1 San Francisco, CA, United States United States
2 Los Angeles, CA, United States United States
3 Sunnyvale, CA, United States United States
4 Sunnyvale, CA, United States United States
5 San Francisco, CA, United States United States
6 Sunnyvale, CA, United States United States
7 Kraków, Poland Poland
8 Shanghai, China China
9 Mountain View, CA, United States United States
10 Boulder, CO, United States United States
11 Boulder, CO, United States United States
12 Xinyi District, Taiwan Taiwan
13 Tel Aviv-Yafo, Israel Israel
14 Wrocław, Poland Poland
15 Singapore Singapore
In [4]: df['Country'].to_dict()
Out[4]:
{0: ' Poland',
1: ' United States',
2: ' United States',
3: ' United States',
4: ' United States',
5: ' United States',
6: ' United States',
7: ' Poland',
8: ' China',
9: ' United States',
10: ' United States',
11: ' United States',
12: ' Taiwan',
13: ' Israel',
14: ' Poland',
15: 'Singapore'}