根据列名称模式 reshape 数据

Question

df <- structure(list(`1.tes1` = 8.00073085700465, `1.tes2` = 8.08008192865136, 
    `1.tes3` = 7.67643993710322, `1.tes4` = 4.40797764861845, 
    `1.tes5` = 8.07887886210789, `1.tes6` = 7.5133416960745, 
    `2.tes1` = 8.85382519278079, `2.tes2` = 7.69705180134625, 
    `2.tes3` = 7.23033538475091, `2.tes4` = 8.14366028991503, 
    `2.tes5` = 8.00207221069391, `2.tes6` = 7.04604929055087, 
    `3.tes1` = 5.56967515444227, `3.tes2` = 6.81971790904382, 
    `3.tes3` = 7.69285459160427, `3.tes4` = 7.29436429730407, 
    `3.tes5` = 7.39693058270568, `3.tes6` = 6.6688956545532, 
    `4.tes1` = 7.02870405956919, `4.tes2` = 7.89704902680482, 
    `4.tes3` = 7.207699266581, `4.tes4` = 8.07642509042209, `4.tes5` = 9.12013776731989, 
    `4.tes6` = 8.73388960806046), row.names = c(NA, -1L), class = c("tbl_df", 
"tbl", "data.frame"))

上面是我的示例数据，列名的模式类似于a.bc，其中a是组ID，b是变量名称，c是复制id，因此3.tes6表示组3，变量tes，复制6.

我想将 df reshape 为一个数据框(更好地使用 tidyverse 包):

Group Variable Replication Value
1     tes      1           8.001
1     tes      2           8.080
...
3     tes      5           7.400
3     tes      6           6.669
...
4     tes      6           8.734

Answer 1

在pivot_longer中使用names_pattern=:

library(dplyr)
library(tidyr)

df %>%
  pivot_longer(everything(), 
               names_to = c("Group", "Variable", "Replication"),
               values_to = "Value",
               names_pattern = "(\\d+)\\.(\\D+)(\\d+)",
               names_transform = list(Group = as.integer, 
                                      Replication = as.integer))

给予:

# A tibble: 24 x 4
   Group Variable Replication Value
   <int> <chr>          <int> <dbl>
 1     1 tes                1  8.00
 2     1 tes                2  8.08
 3     1 tes                3  7.68
 4     1 tes                4  4.41
 5     1 tes                5  8.08
 6     1 tes                6  7.51
 7     2 tes                1  8.85
 8     2 tes                2  7.70
 9     2 tes                3  7.23
10     2 tes                4  8.14
# ... with 14 more rows