Create stacked pandas series from series with list elements

Question

I have a pandas series with elements as list:

import pandas as pd
s = pd.Series([ ['United States of America'],['China', 'Hong Kong'], []])
print(s)

0    [United States of America]
1            [China, Hong Kong]
2                            []

How to get a series like the following:

0 United States of America
1 China
1 Hong Kong

I am not sure about what happens to 2.

Answer 1

The following options all return Series. Create a new frame and listify.

pd.DataFrame(s.tolist()).stack()

0  0    United States of America
1  0                       China
   1                   Hong Kong
dtype: object

To reset the index, use

pd.DataFrame(s.tolist()).stack().reset_index(drop=True)

0    United States of America
1                       China
2                   Hong Kong
dtype: object

To convert to DataFrame, call to_frame()

pd.DataFrame(s.tolist()).stack().reset_index(drop=True).to_frame('countries')

                  countries
0  United States of America
1                     China
2                 Hong Kong

---

If you're trying to code golf, use

sum(s, [])
# ['United States of America', 'China', 'Hong Kong']

pd.Series(sum(s, []))

0    United States of America
1                       China
2                   Hong Kong
dtype: object

Or even,

pd.Series(np.sum(s))

0    United States of America
1                       China
2                   Hong Kong
dtype: object

However, like most other operations involving sums of lists operations, this is bad in terms of performance (list concatenation operations are inefficient).

---

Faster operations are possible using chaining with itertools.chain:

from itertools import chain
pd.Series(list(chain.from_iterable(s)))

0    United States of America
1                       China
2                   Hong Kong
dtype: object

pd.DataFrame(list(chain.from_iterable(s)), columns=['countries'])

                  countries
0  United States of America
1                     China
2                 Hong Kong