transpose-data.R

library(tidyverse)
set.seed(1234)
d <-
  tibble(
    Time = letters[1:5] %>% rep(3),
    Species = LETTERS[1:3] %>% rep(each = 5),
    LS_2 = rpois(15, 1),
    LS_3 = rpois(15, 2),
    LS_4 = rpois(15, 3)
  )

print(d)
# A tibble: 15 × 5
#    Time  Species  LS_2  LS_3  LS_4
#    <chr> <chr>   <int> <int> <int>
#  1 a     A           0     3     3
#  2 b     A           1     1     2
#  3 c     A           1     1     2
#  4 d     A           1     1     3
#  5 e     A           2     1     1
#  6 a     B           1     1     4
#  7 b     B           0     1     2
#  8 c     B           0     1     2
#  9 d     B           1     0     8
# 10 e     B           1     1     4
# 11 a     C           1     3     3
# 12 b     C           1     2     3
# 13 c     C           0     4     2
# 14 d     C           3     3     3
# 15 e     C           0     0     2

d %>%
  # melt/gather 成 long table
  gather("method", "Y", -Time, -Species) %>% 
  # dcast/spread 成新的 wide table
  spread(Species, Y)
# A tibble: 15 × 5
#    Time  method     A     B     C
#    <chr> <chr>  <int> <int> <int>
#  1 a     LS_2       0     1     1
#  2 a     LS_3       3     1     3
#  3 a     LS_4       3     4     3
#  4 b     LS_2       1     0     1
#  5 b     LS_3       1     1     2
#  6 b     LS_4       2     2     3
#  7 c     LS_2       1     0     0
#  8 c     LS_3       1     1     4
#  9 c     LS_4       2     2     2
# 10 d     LS_2       1     1     3
# 11 d     LS_3       1     0     3
# 12 d     LS_4       3     8     3
# 13 e     LS_2       2     1     0
# 14 e     LS_3       1     1     0
# 15 e     LS_4       1     4     2