Transpose dataframe-CodePudding

I have the following data:

structure(list(Tempo = c("t0", "t1", "REC1", "REC2", "REC4", 
"REC8", "REC11"), sig_C = c("a", "a", "a", "a", "a", "a", "a"
), sig_C1 = c("a", "a", "a", "a", "a", "a", "a"), sig_C2 = c("a", 
"a", "a", "a", "a", "a", "a"), sig_C3 = c("a", "a", "a", "a", 
"a", "a", "a"), sig_C4 = c("a", "a", "a", "a", "a", "a", "a"), 
    sig_C5 = c("a", "b", "b", "ab", "ab", "ab", "a")), row.names = c(NA, 
-7L), class = c("tbl_df", "tbl", "data.frame"))

I would to like transpose this data frame, keeping Tempo as column names and sig_C untill sig_C5 as a variable called group.

I try to use t() function, but not work in the desired way.

Thanks

CodePudding user response：

Perhaps something like this to touch up t() result:

library(dplyr)
library(tibble)

dft <- t(df)
colnames(dft) <- dft[1,]
as.data.frame.matrix(dft[-1,]) %>% 
  rownames_to_column("Group") %>% 
  as_tibble()
#> # A tibble: 6 × 8
#>   Group  t0    t1    REC1  REC2  REC4  REC8  REC11
#>   <chr>  <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 sig_C  a     a     a     a     a     a     a    
#> 2 sig_C1 a     a     a     a     a     a     a    
#> 3 sig_C2 a     a     a     a     a     a     a    
#> 4 sig_C3 a     a     a     a     a     a     a    
#> 5 sig_C4 a     a     a     a     a     a     a    
#> 6 sig_C5 a     b     b     ab    ab    ab    a

Input:

df <- structure(list(
  Tempo = c(
    "t0", "t1", "REC1", "REC2", "REC4",
    "REC8", "REC11"
  ), sig_C = c("a", "a", "a", "a", "a", "a", "a"), sig_C1 = c("a", "a", "a", "a", "a", "a", "a"), sig_C2 = c(
    "a",
    "a", "a", "a", "a", "a", "a"
  ), sig_C3 = c(
    "a", "a", "a", "a",
    "a", "a", "a"
  ), sig_C4 = c("a", "a", "a", "a", "a", "a", "a"),
  sig_C5 = c("a", "b", "b", "ab", "ab", "ab", "a")
), row.names = c(
  NA,
  -7L
), class = c("tbl_df", "tbl", "data.frame"))

^{Created on 2023-01-26 with reprex v2.0.2}

CodePudding user response：

You could try using pivot() from the tidyr library to reshape it.

library(tidyr)

df_reshaped <- pivot(data = df, id_cols = Tempo, cols_to_rename = sig_C:sig_C5, values_to = "group")
After running this, you'll have the dataframe with Tempo as columns and sig_C to sig_C5 as variable called group.