R: rehape from "wide" to "long", keeping some variables "wide"-CodePudding

I have data file in wide format, with a set of recurring variables (var1 var2, below)

data have:

| ID | background vars| var1.A | var2.A | var1.B | var2.B | var1.C | var2.C |
| -: | :------------- |:------:|:------:|:------:|:------:|:------:|:------:|
| 1  |  data1         | 1      | 2      | 3      | 4      | 5      | 6      | 
| 2  |  data2         | 7      | 8      | 9      | 10     | 11     | 12     |

I need to reshape it "half way" into to long format, i.e. keep a each var group together (wide), and each recurrence in a different line (long).

data want:

| ID | background vars | recurrence | var1   | var2   |
| -: | :-------------- |:----------:|:------:|:------:|
| 1  |  data1          | A          | 1      | 2      |
| 1  |  data1          | B          | 3      | 4      |
| 1  |  data1          | C          | 5      | 6      |
| 2  |  data2          | A          | 7      | 8      |
| 2  |  data2          | B          | 9      | 10     |
| 2  |  data2          | C          | 11     | 12     |

I found some solutions for this using reshape() gather() and melt(). However, all these collapse ALL variables to long format, and do not allow for some variables to be kept "wide").

How can data be shaped this way using R?

CodePudding user response：

Use the keyword '.value' in the names_to argument to keep that part of the column name in wide format:

tidyr::pivot_longer(df, c(-ID, -`background vars`),
                    names_sep = '\\.', 
                    names_to = c('.value', 'recurrence'))
#> # A tibble: 6 x 5
#>      ID `background vars` recurrence  var1  var2
#>   <int> <chr>             <chr>      <int> <int>
#> 1     1 data1             A              1     2
#> 2     1 data1             B              3     4
#> 3     1 data1             C              5     6
#> 4     2 data2             A              7     8
#> 5     2 data2             B              9    10
#> 6     2 data2             C             11     1

CodePudding user response：

If you need your code to be easily readable/comprehensible and you feel that ".value" in @Allan's example is a little opaque, you might consider a two-step pivot - simply pivot_long() and then immediately pivot_wide() with different parameters:

df <- structure(
  list(
    ID = 1:2,
    background.vars = c("data1", "data2"),
    var1.A = c(1L, 7L),
    var2.A = c(2L, 8L),
    var1.B = c(3L, 9L),
    var2.B = c(4L, 10L),
    var1.C = c(5L, 11L),
    var2.C = c(6L, 12L)),
  class = "data.frame",
  row.names = c(NA, -2L)
)

require(tidyr)
#> Loading required package: tidyr

long.df <- 
  pivot_longer(df, 
             c(-ID, -`background.vars`),
             names_sep = "\\.",
             names_to = c("var", "number"))

long.df
#> # A tibble: 12 × 5
#>       ID background.vars var   number value
#>    <int> <chr>           <chr> <chr>  <int>
#>  1     1 data1           var1  A          1
#>  2     1 data1           var2  A          2
#>  3     1 data1           var1  B          3
#>  4     1 data1           var2  B          4
#>  5     1 data1           var1  C          5
#>  6     1 data1           var2  C          6
#>  7     2 data2           var1  A          7
#>  8     2 data2           var2  A          8
#>  9     2 data2           var1  B          9
#> 10     2 data2           var2  B         10
#> 11     2 data2           var1  C         11
#> 12     2 data2           var2  C         12

pivot_wider(long.df, names_from = "var")
#> # A tibble: 6 × 5
#>      ID background.vars number  var1  var2
#>   <int> <chr>           <chr>  <int> <int>
#> 1     1 data1           A          1     2
#> 2     1 data1           B          3     4
#> 3     1 data1           C          5     6
#> 4     2 data2           A          7     8
#> 5     2 data2           B          9    10
#> 6     2 data2           C         11    12

^{Created on 2022-05-24 by the reprex package (v2.0.1)}