Adding up multiple data frames based on 2 unique identifiers












0















I have ten data frames and I would like to add up them based on id and pnum. What is the best way to do this? Thank you



df1 -example of df1



id pnum v1  v2  v3... v144
111 1 1 0 0 ... 0
111 2 1 1 0 ...0
121 1 1 1 0 ...0
123 2 1 1 0 ...0
123 1 1 1 0 ...0



df3 -example of df3

id pnum v1 v2 v3... v144
111 1 0 0 0 ... 0
111 2 0 0 0 ...1
121 1 0 0 0 ...1
123 2 0 0 0 ...0
123 1 0 0 0 ...1

...

df10 -example of df10

id pnum v1 v2 v3... v144
111 1 0 0 0 ... 0
111 2 0 1 0 ...1
121 1 0 0 1 ...1
123 2 0 1 0 ...0
123 1 0 0 0 ...1









share|improve this question





























    0















    I have ten data frames and I would like to add up them based on id and pnum. What is the best way to do this? Thank you



    df1 -example of df1



    id pnum v1  v2  v3... v144
    111 1 1 0 0 ... 0
    111 2 1 1 0 ...0
    121 1 1 1 0 ...0
    123 2 1 1 0 ...0
    123 1 1 1 0 ...0



    df3 -example of df3

    id pnum v1 v2 v3... v144
    111 1 0 0 0 ... 0
    111 2 0 0 0 ...1
    121 1 0 0 0 ...1
    123 2 0 0 0 ...0
    123 1 0 0 0 ...1

    ...

    df10 -example of df10

    id pnum v1 v2 v3... v144
    111 1 0 0 0 ... 0
    111 2 0 1 0 ...1
    121 1 0 0 1 ...1
    123 2 0 1 0 ...0
    123 1 0 0 0 ...1









    share|improve this question



























      0












      0








      0


      1






      I have ten data frames and I would like to add up them based on id and pnum. What is the best way to do this? Thank you



      df1 -example of df1



      id pnum v1  v2  v3... v144
      111 1 1 0 0 ... 0
      111 2 1 1 0 ...0
      121 1 1 1 0 ...0
      123 2 1 1 0 ...0
      123 1 1 1 0 ...0



      df3 -example of df3

      id pnum v1 v2 v3... v144
      111 1 0 0 0 ... 0
      111 2 0 0 0 ...1
      121 1 0 0 0 ...1
      123 2 0 0 0 ...0
      123 1 0 0 0 ...1

      ...

      df10 -example of df10

      id pnum v1 v2 v3... v144
      111 1 0 0 0 ... 0
      111 2 0 1 0 ...1
      121 1 0 0 1 ...1
      123 2 0 1 0 ...0
      123 1 0 0 0 ...1









      share|improve this question
















      I have ten data frames and I would like to add up them based on id and pnum. What is the best way to do this? Thank you



      df1 -example of df1



      id pnum v1  v2  v3... v144
      111 1 1 0 0 ... 0
      111 2 1 1 0 ...0
      121 1 1 1 0 ...0
      123 2 1 1 0 ...0
      123 1 1 1 0 ...0



      df3 -example of df3

      id pnum v1 v2 v3... v144
      111 1 0 0 0 ... 0
      111 2 0 0 0 ...1
      121 1 0 0 0 ...1
      123 2 0 0 0 ...0
      123 1 0 0 0 ...1

      ...

      df10 -example of df10

      id pnum v1 v2 v3... v144
      111 1 0 0 0 ... 0
      111 2 0 1 0 ...1
      121 1 0 0 1 ...1
      123 2 0 1 0 ...0
      123 1 0 0 0 ...1






      r function dataframe






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      edited Nov 21 '18 at 20:12







      RforDummies

















      asked Nov 21 '18 at 17:49









      RforDummiesRforDummies

      378




      378
























          2 Answers
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          0














          We can get the datasets in a list with mget, use bind_rows to row bind the datasets to a single dataset, grouped by 'id', 'pnum', summarise all the columns (summarise_all) to return the sum for each group



          library(dplyr)
          mget(paste0('df', 1:10)) %>%
          bind_rows %>%
          group_by(id, pnum) %>%
          summarise_all(sum)





          share|improve this answer































            0














            Consider rbind on list of data frames and then run aggregate



            df_list <- list(df1, df2, df3, ..., df10)

            master_df <- do.call(rbind, df_list)

            agg_df <- aggregate(. ~ ID + pnum, master_df, sum)





            share|improve this answer























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              2 Answers
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              active

              oldest

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              2 Answers
              2






              active

              oldest

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              active

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              0














              We can get the datasets in a list with mget, use bind_rows to row bind the datasets to a single dataset, grouped by 'id', 'pnum', summarise all the columns (summarise_all) to return the sum for each group



              library(dplyr)
              mget(paste0('df', 1:10)) %>%
              bind_rows %>%
              group_by(id, pnum) %>%
              summarise_all(sum)





              share|improve this answer




























                0














                We can get the datasets in a list with mget, use bind_rows to row bind the datasets to a single dataset, grouped by 'id', 'pnum', summarise all the columns (summarise_all) to return the sum for each group



                library(dplyr)
                mget(paste0('df', 1:10)) %>%
                bind_rows %>%
                group_by(id, pnum) %>%
                summarise_all(sum)





                share|improve this answer


























                  0












                  0








                  0







                  We can get the datasets in a list with mget, use bind_rows to row bind the datasets to a single dataset, grouped by 'id', 'pnum', summarise all the columns (summarise_all) to return the sum for each group



                  library(dplyr)
                  mget(paste0('df', 1:10)) %>%
                  bind_rows %>%
                  group_by(id, pnum) %>%
                  summarise_all(sum)





                  share|improve this answer













                  We can get the datasets in a list with mget, use bind_rows to row bind the datasets to a single dataset, grouped by 'id', 'pnum', summarise all the columns (summarise_all) to return the sum for each group



                  library(dplyr)
                  mget(paste0('df', 1:10)) %>%
                  bind_rows %>%
                  group_by(id, pnum) %>%
                  summarise_all(sum)






                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 21 '18 at 17:51









                  akrunakrun

                  409k13198273




                  409k13198273

























                      0














                      Consider rbind on list of data frames and then run aggregate



                      df_list <- list(df1, df2, df3, ..., df10)

                      master_df <- do.call(rbind, df_list)

                      agg_df <- aggregate(. ~ ID + pnum, master_df, sum)





                      share|improve this answer




























                        0














                        Consider rbind on list of data frames and then run aggregate



                        df_list <- list(df1, df2, df3, ..., df10)

                        master_df <- do.call(rbind, df_list)

                        agg_df <- aggregate(. ~ ID + pnum, master_df, sum)





                        share|improve this answer


























                          0












                          0








                          0







                          Consider rbind on list of data frames and then run aggregate



                          df_list <- list(df1, df2, df3, ..., df10)

                          master_df <- do.call(rbind, df_list)

                          agg_df <- aggregate(. ~ ID + pnum, master_df, sum)





                          share|improve this answer













                          Consider rbind on list of data frames and then run aggregate



                          df_list <- list(df1, df2, df3, ..., df10)

                          master_df <- do.call(rbind, df_list)

                          agg_df <- aggregate(. ~ ID + pnum, master_df, sum)






                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered Nov 21 '18 at 20:41









                          ParfaitParfait

                          51.9k84470




                          51.9k84470






























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