Transposing a dataframe maintaining the first column as heading

Here is one way

tmydf = setNames(data.frame(t(mydf[,-1])), mydf[,1])

Something like this perhaps:

tmp <- as.data.frame(t(mydf[,-1]))
> colnames(tmp) <- mydf$A
> tmp
    a  b  c  d  e  f  g  h  i  j
M1 11 12 13 14 15 16 17 18 19 20
M2 31 32 33 34 35 36 37 38 39 40
M3 41 42 43 44 45 46 47 48 49 50

You can use the pivot_longer and pivot_wider functions from the tidyr package.

library(tidyr)
mydf%>%
  pivot_longer(cols=c(-A),names_to="Original_Vars")%>%
  pivot_wider(names_from=c(A))

The pivot_longer makes a column called "Original_Vars", and a new column called value. If you stopped here, you'd have a row for each combination of your A variable, your "Original_Vars" (being M1, M2, and M3 here), and the value associated with that pairing.

The pivot_wider then takes all your values from the "A" column and turns them into columns, using the values from the value column we created with pivot_longer to fill in.

One more way using janitor::row_to_names() with dplyr/magrittr pipes

mydf <- data.frame(A = c(letters[1:10]), M1 = c(11:20), M2 = c(31:40), M3 = c(41:50))


library(janitor, warn.conflicts = F)
library(dplyr, warn.conflicts = F)
mydf %>% t %>% as.data.frame() %>% row_to_names(1)

#>     a  b  c  d  e  f  g  h  i  j
#> M1 11 12 13 14 15 16 17 18 19 20
#> M2 31 32 33 34 35 36 37 38 39 40
#> M3 41 42 43 44 45 46 47 48 49 50

^{Created on 2021-06-17 by the reprex package (v2.0.0)}

Data.table variante from Ramnath with indicating in string the variable name wanted.

mydf <- data.table(A = c(letters[1:10]), M1 = c(11:20), M2 = c(31:40), M3 = c(41:50))
tmydf <- setNames(data.table(t(mydf[,-"A"])), mydf[["A"]])

Transposing a dataframe maintaining the first column as heading

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