Data
type id count date name set A AA01 Q4 21 hello set A AA01 Q4 21 hello set A AA01 Q4 21 hello set A AA01 Q4 21 hello no B BB01 Q4 21 hey
Desired
type id count date name full set A AA01 Q4 21 hello A AA01 Q4 21 - hello set A AA01 Q4 21 hello A AA01 Q4 21 - hello set A AA01 Q4 21 hello A AA01 Q4 21 - hello set A AA01 Q4 21 hello A AA01 Q4 21 - hello no B BB01 Q4 21 hey B BB01 Q4 21 - hey
Doing
df['combined']=df['full'].astype(str)+'_'+df['id']+'_'+df['count']
However, the other columns are not being maintained. I am still troubleshooting, any suggestion is appreciated
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Answer
df['full'] = df.apply(lambda row: str(row['id']) + ' ' + str(row['count']) + ' ' + str(row['date']) + ' - ' + str(row['name']), axis=1)