How to take a Pandas series and split it so it gives me the full name

Question

    0
2   ['name:', 'Atlanta', 'GA:', 'Hartsfield-Jackson', 'Atlanta', 'International']
35  ['name:', 'Boston', 'MA:', 'Logan', 'International']
68  ['name:', 'Baltimore', 'MD:', 'Baltimore/Washington', 'International', 'Thurgood', 'Marshall']
101 ['name:', 'Charlotte', 'NC:', 'Charlotte', 'Douglas', 'International']
134 ['name:', 'Washington', 'DC:', 'Ronald', 'Reagan', 'Washington', 'National']
167 ['name:', 'Denver', 'CO:', 'Denver', 'International']
200 ['name:', 'Dallas/Fort', 'Worth', 'TX:', 'Dallas/Fort', 'Worth', 'International']
233 ['name:', 'Detroit', 'MI:', 'Detroit', 'Metro', 'Wayne', 'County']
266 ['name:', 'Newark', 'NJ:', 'Newark', 'Liberty', 'International']
299 ['name:', 'Fort', 'Lauderdale', 'FL:', 'Fort', 'Lauderdale-Hollywood', 'International']
332 ['name:', 'Washington', 'DC:', 'Washington', 'Dulles', 'International']

I have this series above and I want to split each row so that it lists everything like; Atlanta GA: Hartsfield-Jackson Atlanta International. This would be one column in a data frame. Essentially just want to remove the 'name:' at the beginning of each row and then split it so I have the form that I want. I have tried

my_series.str.split("'").str[7].reset_index(drop=True).astype(str)

But my output comes out to

    0
0   Hartsfield-Jackson
1   Logan
2   Baltimore/Washington
3   Charlotte
4   Ronald
5   Denver
6   TX:
7   Detroit
8   Newark
9   FL:
10  Washington

Answer 1

Hey comeyougunners10,

Just as Barmar suggested, you are not dealing with a string; instead, I suspect you are dealing with the list as the value in each cell.

Just do a quick test yourself, and see if the result is a list:

type(df.iloc[index_of_this_column,0])

If you are indeed dealing with lists, then here is how I will approach it.

def pandas_list_str_spliter(input_value):
    # we use the join function to turn list into the str
    # From here, you should be able to do any transformation you need 
    # I only removed the "name:" and front & tailing whitespace.
    # But you can modify the function to suit your need
    return ' '.join(input_value).replace('name:','').strip()

df['Column_Split'] = df['Column_Split'].apply(pandas_list_str_spliter)

I hope this can be helpful.