Pandas Dataframe Merging

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I have a bit of a weird pandas question.



I have a master Dataframe:



   a   b   c
0 22 44 55
1 22 45 22
2 44 23 56
3 45 22 33


I then have a dataframe in a different dimension which has some over lapping index's and column names



index   col_name  new_value
0 a 111
3 b 234


I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.



So the output would be



   a   b   c
0 111 44 55
1 22 45 22
2 44 23 56
3 45 234 33


I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)










share|improve this question



























    0














    I have a bit of a weird pandas question.



    I have a master Dataframe:



       a   b   c
    0 22 44 55
    1 22 45 22
    2 44 23 56
    3 45 22 33


    I then have a dataframe in a different dimension which has some over lapping index's and column names



    index   col_name  new_value
    0 a 111
    3 b 234


    I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.



    So the output would be



       a   b   c
    0 111 44 55
    1 22 45 22
    2 44 23 56
    3 45 234 33


    I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)










    share|improve this question

























      0












      0








      0







      I have a bit of a weird pandas question.



      I have a master Dataframe:



         a   b   c
      0 22 44 55
      1 22 45 22
      2 44 23 56
      3 45 22 33


      I then have a dataframe in a different dimension which has some over lapping index's and column names



      index   col_name  new_value
      0 a 111
      3 b 234


      I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.



      So the output would be



         a   b   c
      0 111 44 55
      1 22 45 22
      2 44 23 56
      3 45 234 33


      I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)










      share|improve this question













      I have a bit of a weird pandas question.



      I have a master Dataframe:



         a   b   c
      0 22 44 55
      1 22 45 22
      2 44 23 56
      3 45 22 33


      I then have a dataframe in a different dimension which has some over lapping index's and column names



      index   col_name  new_value
      0 a 111
      3 b 234


      I'm trying to then say if you find a match on index and col_name in the master dataframe, then replace the value.



      So the output would be



         a   b   c
      0 111 44 55
      1 22 45 22
      2 44 23 56
      3 45 234 33


      I've found "Combine_first" but this doesn't work unless I pivot the second dataframe (which I can't do in this scenario)







      pandas merge






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Dec 27 '18 at 16:34









      fred.schwartz

      3048




      3048
























          1 Answer
          1






          active

          oldest

          votes


















          5














          This is update problem



          df.update(updated.pivot(*updated.columns))
          df
          Out[479]:
          a b c
          0 111.0 44.0 55
          1 22.0 45.0 22
          2 44.0 23.0 56
          3 45.0 234.0 33


          Or



          df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
          df
          Out[495]:
          a b c
          0 111 44 55
          1 22 45 22
          2 44 23 56
          3 45 234 33





          share|improve this answer





















          • Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
            – fred.schwartz
            Dec 27 '18 at 16:40






          • 1




            Wow. This is cool. +1
            – Scott Boston
            Dec 27 '18 at 16:40






          • 1




            @ScottBoston thank you man
            – W-B
            Dec 27 '18 at 16:41






          • 1




            @fred.schwartz yes , it is
            – W-B
            Dec 27 '18 at 16:42






          • 1




            @coldspeed thank you so much ! Without your support, this would not have been possible!
            – W-B
            Dec 27 '18 at 16:51













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          1 Answer
          1






          active

          oldest

          votes








          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          5














          This is update problem



          df.update(updated.pivot(*updated.columns))
          df
          Out[479]:
          a b c
          0 111.0 44.0 55
          1 22.0 45.0 22
          2 44.0 23.0 56
          3 45.0 234.0 33


          Or



          df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
          df
          Out[495]:
          a b c
          0 111 44 55
          1 22 45 22
          2 44 23 56
          3 45 234 33





          share|improve this answer





















          • Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
            – fred.schwartz
            Dec 27 '18 at 16:40






          • 1




            Wow. This is cool. +1
            – Scott Boston
            Dec 27 '18 at 16:40






          • 1




            @ScottBoston thank you man
            – W-B
            Dec 27 '18 at 16:41






          • 1




            @fred.schwartz yes , it is
            – W-B
            Dec 27 '18 at 16:42






          • 1




            @coldspeed thank you so much ! Without your support, this would not have been possible!
            – W-B
            Dec 27 '18 at 16:51


















          5














          This is update problem



          df.update(updated.pivot(*updated.columns))
          df
          Out[479]:
          a b c
          0 111.0 44.0 55
          1 22.0 45.0 22
          2 44.0 23.0 56
          3 45.0 234.0 33


          Or



          df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
          df
          Out[495]:
          a b c
          0 111 44 55
          1 22 45 22
          2 44 23 56
          3 45 234 33





          share|improve this answer





















          • Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
            – fred.schwartz
            Dec 27 '18 at 16:40






          • 1




            Wow. This is cool. +1
            – Scott Boston
            Dec 27 '18 at 16:40






          • 1




            @ScottBoston thank you man
            – W-B
            Dec 27 '18 at 16:41






          • 1




            @fred.schwartz yes , it is
            – W-B
            Dec 27 '18 at 16:42






          • 1




            @coldspeed thank you so much ! Without your support, this would not have been possible!
            – W-B
            Dec 27 '18 at 16:51
















          5












          5








          5






          This is update problem



          df.update(updated.pivot(*updated.columns))
          df
          Out[479]:
          a b c
          0 111.0 44.0 55
          1 22.0 45.0 22
          2 44.0 23.0 56
          3 45.0 234.0 33


          Or



          df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
          df
          Out[495]:
          a b c
          0 111 44 55
          1 22 45 22
          2 44 23 56
          3 45 234 33





          share|improve this answer












          This is update problem



          df.update(updated.pivot(*updated.columns))
          df
          Out[479]:
          a b c
          0 111.0 44.0 55
          1 22.0 45.0 22
          2 44.0 23.0 56
          3 45.0 234.0 33


          Or



          df.values[updated['index'].values,df.columns.get_indexer(updated.col_name)]=updated.new_value.values
          df
          Out[495]:
          a b c
          0 111 44 55
          1 22 45 22
          2 44 23 56
          3 45 234 33






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Dec 27 '18 at 16:36









          W-B

          101k73163




          101k73163












          • Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
            – fred.schwartz
            Dec 27 '18 at 16:40






          • 1




            Wow. This is cool. +1
            – Scott Boston
            Dec 27 '18 at 16:40






          • 1




            @ScottBoston thank you man
            – W-B
            Dec 27 '18 at 16:41






          • 1




            @fred.schwartz yes , it is
            – W-B
            Dec 27 '18 at 16:42






          • 1




            @coldspeed thank you so much ! Without your support, this would not have been possible!
            – W-B
            Dec 27 '18 at 16:51




















          • Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
            – fred.schwartz
            Dec 27 '18 at 16:40






          • 1




            Wow. This is cool. +1
            – Scott Boston
            Dec 27 '18 at 16:40






          • 1




            @ScottBoston thank you man
            – W-B
            Dec 27 '18 at 16:41






          • 1




            @fred.schwartz yes , it is
            – W-B
            Dec 27 '18 at 16:42






          • 1




            @coldspeed thank you so much ! Without your support, this would not have been possible!
            – W-B
            Dec 27 '18 at 16:51


















          Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
          – fred.schwartz
          Dec 27 '18 at 16:40




          Thank you. My fault for not labelling but in your example is df the master dataframe and updated the one to add on?
          – fred.schwartz
          Dec 27 '18 at 16:40




          1




          1




          Wow. This is cool. +1
          – Scott Boston
          Dec 27 '18 at 16:40




          Wow. This is cool. +1
          – Scott Boston
          Dec 27 '18 at 16:40




          1




          1




          @ScottBoston thank you man
          – W-B
          Dec 27 '18 at 16:41




          @ScottBoston thank you man
          – W-B
          Dec 27 '18 at 16:41




          1




          1




          @fred.schwartz yes , it is
          – W-B
          Dec 27 '18 at 16:42




          @fred.schwartz yes , it is
          – W-B
          Dec 27 '18 at 16:42




          1




          1




          @coldspeed thank you so much ! Without your support, this would not have been possible!
          – W-B
          Dec 27 '18 at 16:51






          @coldspeed thank you so much ! Without your support, this would not have been possible!
          – W-B
          Dec 27 '18 at 16:51




















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