Add new row to dataframe at specific row-index not appended

Question

The following code combines a vector with a dataframe   newrow   c 1 4  existingDF   rbind existingDF newrow    However this code always inserts the new row at the end of the dataframe   How can I insert the row at a specified point within the dataframe  For example  lets say the dataframe has 20 rows  how can I insert the new row between rows 10 and 11

User · Answer

The  before argument in dplyr  add row can be used to specify the row  dplyr  add row    cars    speed   0    dist   0     before   3     gt     speed dist   gt  1      4    2   gt  2      4   10   gt  3      0    0   gt  4      7    4   gt  5      7   22   gt  6      8   16   gt

User · Answer

for example you want to add rows of variable 2 to variable 1 of a data named  edges   just do it like this  allEdges  lt - data frame c edges V1 edges V2

User · Answer

Here s a solution that avoids the  often slow  rbind call   existingDF  lt - as data frame matrix seq 20  nrow 5 ncol 4   r  lt - 3 newrow  lt - seq 4  insertRow  lt - function existingDF  newrow  r      existingDF seq r 1 nrow existingDF  1     lt - existingDF seq r nrow existingDF       existingDF r    lt - newrow   existingDF     gt  insertRow existingDF  newrow  r    V1 V2 V3 V4 1  1  6 11 16 2  2  7 12 17 3  1  2  3  4 4  3  8 13 18 5  4  9 14 19 6  5 10 15 20   If speed is less important than clarity  then  Simon s solution works well   existingDF  lt - rbind existingDF 1 r   newrow existingDF - 1 r      gt  existingDF    V1 V2 V3 V4 1   1  6 11 16 2   2  7 12 17 3   3  8 13 18 4   1  2  3  4 41  4  9 14 19 5   5 10 15 20    Note we index r differently    And finally  benchmarks   library microbenchmark  microbenchmark    rbind existingDF 1 r   newrow existingDF - 1 r        insertRow existingDF newrow r     Unit  microseconds                                                     expr     min       lq   median       uq       max 1                       insertRow existingDF  newrow  r  660 131 678 3675 695 5515 725 2775   928 299 2 rbind existingDF 1 r     newrow  existingDF - 1 r      801 161 831 7730 854 6320 881 6560 10641 417   Benchmarks  As  MatthewDowle always points out to me  benchmarks need to be examined for the scaling as the size of the problem increases   Here we go then   benchmarkInsertionSolutions  lt - function nrow 5 ncol 4      existingDF  lt - as data frame matrix seq nrow ncol  nrow nrow ncol ncol     r  lt - 3   Row to insert into   newrow  lt - seq ncol    m  lt - microbenchmark     rbind existingDF 1 r   newrow existingDF - 1 r         insertRow existingDF newrow r      insertRow2 existingDF newrow r          Now return the median times   mediansBy  lt - by m time m expr  FUN median    res  lt - as numeric mediansBy    names res   lt - names mediansBy    res   nrows  lt - 5 10  0 5  benchmarks  lt - sapply nrows benchmarkInsertionSolutions  colnames benchmarks   lt - as character nrows  ggplot  melt benchmarks   aes x Var2 y value colour Var1      geom line     scale x log10     scale y log10      Roland s solution scales quite well  even with the call to rbind                                                                 5       50     500    5000    50000     5e 05 insertRow2 existingDF  newrow  r                       549861 5 579579 0  789452 2512926 46994560 414790214 insertRow existingDF  newrow  r                        895401 0 905318 5 1168201 2603926 39765358 392904851 rbind existingDF 1 r     newrow  existingDF - 1 r      787218 0 814979 0 1263886 5591880 63351247 829650894   Plotted on a linear scale     And a log-log scale

User · Answer

insertRow2  lt - function existingDF  newrow  r      existingDF  lt - rbind existingDF newrow    existingDF  lt - existingDF order c 1  nrow existingDF -1  r-0 5       row names existingDF   lt - 1 nrow existingDF    return existingDF       insertRow2 existingDF newrow r     V1 V2 V3 V4 1  1  6 11 16 2  2  7 12 17 3  1  2  3  4 4  3  8 13 18 5  4  9 14 19 6  5 10 15 20  microbenchmark      rbind existingDF 1 r   newrow existingDF - 1 r          insertRow existingDF newrow r       insertRow2 existingDF newrow r      Unit  microseconds                                                     expr     min       lq   median       uq      max 1                       insertRow existingDF  newrow  r  513 157 525 6730 531 8715 544 4575 1409 553 2                      insertRow2 existingDF  newrow  r  430 664 443 9010 450 0570 461 3415  499 988 3 rbind existingDF 1 r     newrow  existingDF - 1 r      606 822 625 2485 633 3710 653 1500 1489 216

User · Answer

You should try dplyr package  library dplyr  a  lt - data frame A   c 1  2  3  4                  B   c 11  12  13  14     system time   for  i in 50 1000        b  lt - data frame A   i  B   i   i      a  lt - bind rows a  b          Output     user  system elapsed     0 25    0 00    0 25   In contrast with using rbind function  a  lt - data frame A   c 1  2  3  4                   B   c 11  12  13  14     system time       for  i in 50 1000            b  lt - data frame A   i  B   i   i          a  lt - rbind a  b              Output     user  system elapsed     0 49    0 00    0 49    There is some performance gain

[r] Add new row to dataframe, at specific row-index, not appended?

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