library(tidyverse)

demo <- tibble(variable=1:16,
               id1=rnorm(16),
               id2=rnorm(16),
               id3=rnorm(16),
               id4=rnorm(16))

# 每 N 列觀察值為一組資料
# 假設 N = 4

n = 4

(demo <- demo %>%
  mutate(group = ceiling(row_number()/n)) |>
  group_split(group))

#> [[1]]
#> # A tibble: 4 × 6
#>   variable     id1    id2    id3    id4 group
#>      <int>   <dbl>  <dbl>  <dbl>  <dbl> <dbl>
#> 1        1 -0.0928  0.701  0.483  0.745     1
#> 2        2  0.821   0.476 -0.627  0.946     1
#> 3        3 -0.269  -0.208  0.991  0.553     1
#> 4        4  0.690  -0.651  0.469 -0.781     1
#>
#> [[2]]
#> # A tibble: 4 × 6
#>   variable    id1     id2    id3    id4 group
#>      <int>  <dbl>   <dbl>  <dbl>  <dbl> <dbl>
#> 1        5 -1.47  -1.59    0.667 -0.378     2
#> 2        6 -0.139 -1.38    0.447 -0.343     2
#> 3        7 -0.532 -0.770  -0.594 -1.91      2
#> 4        8 -0.895 -0.0286  2.34  -0.115     2
#>
#> [[3]]
#> # A tibble: 4 × 6
#>   variable    id1    id2    id3    id4 group
#>      <int>  <dbl>  <dbl>  <dbl>  <dbl> <dbl>
#> 1        9 -0.299  0.487 -1.23  -1.41      3
#> 2       10 -0.114 -0.478  0.895 -1.10      3
#> 3       11 -0.190  0.463 -0.339 -0.294     3
#> 4       12 -0.596 -1.88  -0.393  1.00      3
#>
#> [[4]]
#> # A tibble: 4 × 6
#>   variable    id1    id2     id3    id4 group
#>      <int>  <dbl>  <dbl>   <dbl>  <dbl> <dbl>
#> 1       13 -0.370 -1.00  -0.0353 -1.58      4
#> 2       14  0.607  0.177  0.252  -0.756     4
#> 3       15 -1.88  -1.25  -0.973   1.10      4
#> 4       16  1.17  -1.27   0.868  -1.30      4


# 儲存為 length(demo) 個資料檔並刪除 group column
for (i in 1:length(demo)) {
  write_csv(select(demo[[i]], -group), paste0(i, ".csv"))
}