在列标题和成对变量中嵌入数据的数据透视表 [英] Pivot table with embedded data in column headings and paired variables

问题描述

假设我有这样的数据，不幸的是在列名中嵌入了变量值:

Say I had data like this with variable values unfortunately embedded in the column names:

library(tidyr)
library(dplyr)
dat <- tribble(
  ~group, ~var1, ~var_meta1, ~var2, ~var_meta2,
  "group1", 5.2, "cat", 4.3, "dog"
)
dat
#> # A tibble: 1 x 5
#>   group   var1 var_meta1  var2 var_meta2
#>   <chr>  <dbl> <chr>     <dbl> <chr>    
#> 1 group1   5.2 cat         4.3 dog

我想将该数据转入其中，以便将列名中的数字作为变量.同时我想保持配对变量(var* 和 var_meta*)之间的关系.

I'd like to pivot that data into this so that the number in the column name because a variable. At the same time I'd like to maintain the relationship between the paired variables (var* and var_meta*) .

#> # A tibble: 2 x 4
#>   group    day   var var_meta
#>   <chr>  <dbl> <dbl> <chr>   
#> 1 group1     1   5.2 cat     
#> 2 group1     2   4.3 dog

对于这种特殊情况，我真的只对 tidyr 解决方案感兴趣.我试过这个:

For this particular case I am really interested in a tidyr solution only. I've tried this:

dat %>%
  pivot_longer(-group,
    names_to = c("day", "var", ".value"),
    names_pattern = "([A-Za-z]+)_([A-Za-z]+)([0-9]+)"
  )
#> # A tibble: 3 x 5
#>   group  day   var   `1`   `2`  
#>   <chr>  <chr> <chr> <chr> <chr>
#> 1 group1 <NA>  <NA>  <NA>  <NA> 
#> 2 group1 var   meta  cat   dog  
#> 3 group1 <NA>  <NA>  <NA>  <NA>

还有这个:

dat %>%
  mutate(across(contains("var"), as.character)) %>%
  pivot_longer(-group,
    names_to = c("type", ".value"),
    names_pattern = "([A-Za-z]+)([0-9]+)"
  )
#> # A tibble: 2 x 4
#>   group  type  `1`   `2`  
#>   <chr>  <chr> <chr> <chr>
#> 1 group1 var   5.2   4.3  
#> 2 group1 meta  cat   dog

我觉得我很接近，但我无法完全理解正则表达式(我认为).

I feel like I am close but I can't quite wrap my head around the regex (I think).

有什么想法吗?

推荐答案

一个选项可能是:

dat %>%
 pivot_longer(-group,
              names_to = c(".value", "day"),
              names_pattern = "(\\D+)(\\d+)")

  group  day     var var_meta
  <chr>  <chr> <dbl> <chr>   
1 group1 1       5.2 cat     
2 group1 2       4.3 dog

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