Match keywords in pandas column with another list of elements

Question

I have a pandas dataframe as:

word_list
[\'nuclear\',\'election\',\'usa\',\'baseball\']
[\'football\',\'united\',\'thriller\']
[\'marvels\',\'hollywood\',\'s         


        

Answer 1

You can flatten dictionary of lists first and then lookup by .get with miscellaneous for non matched values, then convert to sets for unique categories and convert to strings by join:

movies=['spiderman','marvels','thriller']
sports=['baseball','hockey','football']
politics=['election','china','usa']
d = {'movies':movies, 'sports':sports, 'politics':politics}
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}

f = lambda x: ','.join(set([d1.get(y, 'miscellaneous') for y in x]))
df['matched_list_names'] = df['word_list'].apply(f)
print (df)

                                 word_list             matched_list_names
0       [nuclear, election, usa, baseball]  politics,miscellaneous,sports
1             [football, united, thriller]    miscellaneous,sports,movies
2  [marvels, hollywood, spiderman, budget]           miscellaneous,movies

Similar solution with list comprehension:

df['matched_list_names'] = [','.join(set([d1.get(y, 'miscellaneous') for y in x])) 
                            for x in df['word_list']]