Pandas Dataframe: split column into multiple columns, right-align inconsistent cell entries

I'd do something like the following:

foo = lambda x: pd.Series([i for i in reversed(x.split(','))])
rev = df['City, State, Country'].apply(foo)
print rev

      0    1        2
0   HUN  NaN      NaN
1   ESP  NaN      NaN
2   GBR  NaN      NaN
3   ESP  NaN      NaN
4   FRA  NaN      NaN
5   USA   ID      NaN
6   USA   GA      NaN
7   USA   NJ  Hoboken
8   USA   NJ      NaN
9   AUS  NaN      NaN

I think that gets you what you want but if you also want to pretty things up and get a City, State, Country column order, you could add the following:

rev.rename(columns={0:'Country',1:'State',2:'City'},inplace=True)
rev = rev[['City','State','Country']]
print rev

     City State Country
0      NaN   NaN     HUN
1      NaN   NaN     ESP
2      NaN   NaN     GBR
3      NaN   NaN     ESP
4      NaN   NaN     FRA
5      NaN    ID     USA
6      NaN    GA     USA
7  Hoboken    NJ     USA
8      NaN    NJ     USA
9      NaN   NaN     AUS

Assume you have the column name as target

df[["City", "State", "Country"]] = df["target"].str.split(pat=",", expand=True)

Since you are dealing with strings I would suggest the amendment to your current code i.e.

location_df = df[['City, State, Country']].apply(lambda x: pd.Series(str(x).split(',')))

I got mine to work by testing one of the columns but give this one a try.