I have the following dataframe in pandas and want to write a statement to compare person-name with new-person and print identifier , person-name, new-identifier , new-person

Basically need to find sidney crosby and crosby sidney in the same data frame. I guess the logic would be if person-name = sidney crosby and new-person = crosby sidney, the output would be:

 df[person-name].equals(df[new-person]) 

wouldn't work since I'm comparing contents in the column rather than the entire column. How can I compare the contents of those 2 columns and print the 4 columns

CodePudding user response：

here is one to way to do it

split the names and sort each of the two 'person-name' and 'new-person' and then compare the sorted names

df[
    df['person-name']
    .apply(lambda x:  ' '.join(sorted(x.split(' '))))
    .eq(
    df['new-person']
        .replace(r'-',' ',regex=True)
        .apply(lambda x:  ' '.join(sorted(x.split(' ')))))][
    ['identifier','person-name','new-identifier','new-person']
]

    identifier       person-name    new-identifier       new-person
1   (hockey, player) sidney crosby  (pittsburg, player)  crosby sidney
2   (hockey, player) wayne gretzky  (oilers, player)     gretzky-wayne
3   (hockey, player) wayne gretzky  (oilers, player)     gretzky-wayne

to keep only the unique, assign the result to another DF and then keep only non duplicated rows

df2=df[
    df['person-name']
    .apply(lambda x:  ' '.join(sorted(x.split(' '))))
    .eq(
    df['new-person']
        .replace(r'-',' ',regex=True)
        .apply(lambda x:  ' '.join(sorted(x.split(' ')))))][
    ['identifier','person-name','new-identifier','new-person']
]
df2[~df2.duplicated(keep='first')]

    identifier       person-name    new-identifier      new-person
1   (hockey, player) sidney crosby  (pittsburg, player) crosby sidney
2   (hockey, player) wayne gretzky  (oilers, player)    gretzky-wayne