Repeat rows of a data frame

Question

I want to repeat the rows of a data frame  each N times  The result should be a new data frame  with nrow new df     nrow old df    N  keeping the data types of the columns   Example for N   2                           A B   C   A B   C             1 j i 100 1 j i 100     -- gt      2 j i 100 2 K P 101             3 K P 101                       4 K P 101   So  each row is repeated 2 times and characters remain characters  factors remain factors  numerics remain numerics       My first attempt used apply  apply old df  2  function co  rep co  each   N    but this one transforms my values to characters and I get        A   B   C      1    j   i   100   2    j   i   100   3    K   P   101   4    K   P   101

User · Answer

Another way to do this would to first get row indices, append extra copies of the df, and then order by the indices:

df$index = 1:nrow(df)
df = rbind(df,df)
df = df[order(df$index),][,-ncol(df)]

Although the other solutions may be shorter, this method may be more advantageous in certain situations.

User · Answer

For reference and adding to answers citing mefa  it might worth to take a look on the implementation of mefa  rep data frame   in case you don t want to include the whole package    gt  data  lt - data frame a letters 1 3   b letters 4 6    gt  data   a b 1 a d 2 b e 3 c f  gt  as data frame lapply data  rep  2     a b 1 a d 2 b e 3 c f 4 a d 5 b e 6 c f

User · Answer

A clean dplyr solution  taken from here  library dplyr  df  lt - tibble x   1 2  y   c  a    b    df   gt   slice rep 1 n    each   2

User · Answer

Adding to what  dardisco mentioned about mefa  rep data frame    it s very flexible   You can either repeat each row N times   rep df  each N    or repeat the entire dataframe N times  think  like when you recycle a vectorized argument   rep df  times N    Two thumbs up for mefa  I had never heard of it until now and I had to write manual code to do this

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My solution similar as mefa   rep data frame  but a little faster and cares about row names   rep data frame  lt - function x  times        rnames  lt - attr x   row names       x  lt - lapply x  rep int  times   times      class x   lt -  data frame      if   is numeric rnames           attr x   row names    lt - make unique rep int rnames  times       else         attr x   row names    lt -  set row names length rnames    times      x     Compare solutions   library Lahman  library microbenchmark  microbenchmark      mefa   rep data frame Batting  10       rep data frame Batting  10       Batting rep int seq len nrow Batting    10          times   10     gt  Unit  milliseconds   gt                                             expr       min       lq     mean   median        uq       max neval cld   gt               mefa   rep data frame Batting  10  127 77786 135 3480 198 0240 148 1749  278 1066  356 3210    10  a    gt                      rep data frame Batting  10   79 70335  82 8165 134 0974  87 2587  191 1713  307 4567    10  a    gt   Batting rep int seq len nrow Batting    10     895 73750 922 7059 981 8891 956 3463 1018 2411 1127 3927    10   b

User · Answer

df  lt - data frame a   1 2  b   letters 1 2    df rep seq len nrow df    each   2

User · Answer

If you can repeat the whole thing  or subset it first then repeat that  then this similar question may be helpful  Once again   library mefa  rep mtcars 10     or simply  mefa   rep data frame mtcars

User · Answer

There is a lovely vectorized solution that repeats only certain rows n-times each  possible for example by adding an ntimes column to your data frame     A B   C ntimes 1 j i 100      2 2 K P 101      4 3 Z Z 102      1   Method   df  lt - data frame A c  j   K   Z    B c  i   P   Z    C c 100 101 102   ntimes c 2 4 1   df  lt - as data frame lapply df  rep  df ntimes     Result     A B   C ntimes 1 Z Z 102      1 2 j i 100      2 3 j i 100      2 4 K P 101      4 5 K P 101      4 6 K P 101      4 7 K P 101      4   This is very similar to Josh O Brien and Mark Miller s method   df rep seq len nrow df    df ntimes      However  that method appears quite a bit slower   df  lt - data frame A c  j   K   Z    B c  i   P   Z    C c 100 101 102   ntimes c 2000 3000 4000    microbenchmark  microbenchmark    df rep seq len nrow df    df ntimes       as data frame lapply df  rep  df ntimes      times   10     Result   Unit  microseconds                                       expr      min       lq      mean   median       uq      max neval    df rep seq len nrow df    df ntimes     3563 113 3586 873 3683 7790 3613 702 3657 063 4326 757    10  as data frame lapply df  rep  df ntimes    625 552  654 638  676 4067  668 094  681 929  799 893    10

User · Answer

try using for example  N 2 rep 1 4  each   N     as an index

User · Answer

The rep row function seems to sometimes make lists for columns  which leads to bad memory hijinks   I have written the following which seems to work well   library plyr  rep row  lt - function r  n     colwise function x  rep x  n   r

[r] Repeat rows of a data.frame

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