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 JavaScript questions and answers, JavaScript questions pdf, JavaScript question bank, JavaScript questions and answers pdf, mcq on JavaScript pdf, JavaScript questions and solutions, JavaScript mcq Test , Interview JavaScript questions, JavaScript Questions for Interview, JavaScript MCQ (Multiple Choice Questions)

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.