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How do I create a new column which is the max of another column where similar values grouped together in Pandas Dataframe?



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0















I have a python dataframe as follows:



AssignmentID Student Assignment_submitted Passed
1 stud1 1 1
2 stud2 1 1
3 stud3 1 1
4 stud1 2 0
5 stud4 1 1
6 stud1 3 0


What I want to do is convert this into following dataframe:



AssignmentID Student Assignment_submitted Passed TotalSubmitted 
1 stud1 1 1 3
2 stud2 1 1 1
3 stud3 1 1 1
4 stud1 2 0 3
5 stud4 1 1 1
6 stud1 3 0 3










share|improve this question




























    0















    I have a python dataframe as follows:



    AssignmentID Student Assignment_submitted Passed
    1 stud1 1 1
    2 stud2 1 1
    3 stud3 1 1
    4 stud1 2 0
    5 stud4 1 1
    6 stud1 3 0


    What I want to do is convert this into following dataframe:



    AssignmentID Student Assignment_submitted Passed TotalSubmitted 
    1 stud1 1 1 3
    2 stud2 1 1 1
    3 stud3 1 1 1
    4 stud1 2 0 3
    5 stud4 1 1 1
    6 stud1 3 0 3










    share|improve this question
























      0












      0








      0








      I have a python dataframe as follows:



      AssignmentID Student Assignment_submitted Passed
      1 stud1 1 1
      2 stud2 1 1
      3 stud3 1 1
      4 stud1 2 0
      5 stud4 1 1
      6 stud1 3 0


      What I want to do is convert this into following dataframe:



      AssignmentID Student Assignment_submitted Passed TotalSubmitted 
      1 stud1 1 1 3
      2 stud2 1 1 1
      3 stud3 1 1 1
      4 stud1 2 0 3
      5 stud4 1 1 1
      6 stud1 3 0 3










      share|improve this question














      I have a python dataframe as follows:



      AssignmentID Student Assignment_submitted Passed
      1 stud1 1 1
      2 stud2 1 1
      3 stud3 1 1
      4 stud1 2 0
      5 stud4 1 1
      6 stud1 3 0


      What I want to do is convert this into following dataframe:



      AssignmentID Student Assignment_submitted Passed TotalSubmitted 
      1 stud1 1 1 3
      2 stud2 1 1 1
      3 stud3 1 1 1
      4 stud1 2 0 3
      5 stud4 1 1 1
      6 stud1 3 0 3







      python pandas






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Mar 22 at 2:43









      Kishore LKishore L

      607




      607






















          1 Answer
          1






          active

          oldest

          votes


















          2














          Check with transform



          df['TotalSubmitted']=df.groupby('Student')['Assignment_submitted'].transform('count')





          share|improve this answer























            Your Answer






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            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2














            Check with transform



            df['TotalSubmitted']=df.groupby('Student')['Assignment_submitted'].transform('count')





            share|improve this answer



























              2














              Check with transform



              df['TotalSubmitted']=df.groupby('Student')['Assignment_submitted'].transform('count')





              share|improve this answer

























                2












                2








                2







                Check with transform



                df['TotalSubmitted']=df.groupby('Student')['Assignment_submitted'].transform('count')





                share|improve this answer













                Check with transform



                df['TotalSubmitted']=df.groupby('Student')['Assignment_submitted'].transform('count')






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Mar 22 at 2:45









                Wen-BenWen-Ben

                124k83771




                124k83771





























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