Converting rows into columns and columns into rows using R

Question

I have a dataframe with unique row names and unique column names  I want to convert the rows into columns and column into rows   For example  this code   starting df  lt - data frame row names  c LETTERS 1 4                              a   c 1 4                             b   seq 0 02 0 08 by 0 02                             c   c  Aaaa   Bbbb   Cccc   Dddd                       results in the following    gt  starting df   a    b    c A 1 0 02 Aaaa B 2 0 04 Bbbb C 3 0 06 Cccc D 4 0 08 Dddd   I want to convert it into another data frame containing exactly the same data  except that what were formerly rows were now columns and vice versa    gt  final df      A    B    C    D a    1    2    3    4 b 0 02 0 04 0 06 0 08 c Aaaa Bbbb Cccc Dddd

User · Answer

Simply use the base transpose function t  wrapped with as data frame   final df  lt - as data frame t starting df   final df      A    B    C    D a    1    2    3    4 b 0 02 0 04 0 06 0 08 c Aaaa Bbbb Cccc Dddd   Above updated  As docendo discimus pointed out  t returns a matrix  As Mark suggested wrapping it with as data frame gets back a data frame instead of a matrix  Thanks

User · Answer

Here is a tidyverse option that might work depending on the data  and some caveats on its usage   library tidyverse   starting df   gt      rownames to column     gt      gather variable  value  -rowname    gt      spread rowname  value    rownames to column   is necessary if the original dataframe has meaningful row names  otherwise the new column names in the new transposed dataframe will be integers corresponding to the orignal row number  If there are no meaningful row names you can skip rownames to column   and replace rowname with the name of the first column in the dataframe  assuming those values are unique and meaningful  Using the tidyr  smiths sample data would be   smiths   gt        gather variable  value  -subject    gt        spread subject  value    Using the example starting df with the tidyverse approach will throw a warning message about dropping attributes  This is related to converting columns with different attribute types into a single character column  The smiths data will not give that warning because all columns except for subject are doubles      The earlier answer using as data frame t    will convert everything to a factor  if there are mixed column types unless stringsAsFactors   FALSE is added   whereas the tidyverse option converts everything to a character by default if  there are mixed column types

[r] Converting rows into columns and columns into rows using R

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