Select column to be last

[jrosen48]

Brief description of the problem

Using dplyr, it is easy to select a column to be ordered first (i.e., the first column from the left side), or to order all of the columns, but it seems like there is not a straightforward way to select a column to be ordered last (i.e., the first from the right side).

For example, if I run the following, Sepal.Length is still the first column:

library(dplyr)
iris <- tbl_df(iris)
iris <- select(iris, everything(), Sepal.Length)

Here is the output:

> iris
# A tibble: 150 x 5
   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
          <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
 1          5.1         3.5          1.4         0.2  setosa
 2          4.9         3.0          1.4         0.2  setosa
 3          4.7         3.2          1.3         0.2  setosa
 4          4.6         3.1          1.5         0.2  setosa
 5          5.0         3.6          1.4         0.2  setosa
 6          5.4         3.9          1.7         0.4  setosa
 7          4.6         3.4          1.4         0.3  setosa
 8          5.0         3.4          1.5         0.2  setosa
 9          4.4         2.9          1.4         0.2  setosa
10          4.9         3.1          1.5         0.1  setosa
# ... with 140 more rows

There is the following work-around given in an answer to this Stack Overflow question, however this seems counter-intuitive:

iris <- select(iris, everything(), -Sepal.Length, Sepal.Length)

Here is the output:

> iris
# A tibble: 150 x 5
   Sepal.Width Petal.Length Petal.Width Species Sepal.Length
         <dbl>        <dbl>       <dbl>  <fctr>        <dbl>
 1         3.5          1.4         0.2  setosa          5.1
 2         3.0          1.4         0.2  setosa          4.9
 3         3.2          1.3         0.2  setosa          4.7
 4         3.1          1.5         0.2  setosa          4.6
 5         3.6          1.4         0.2  setosa          5.0
 6         3.9          1.7         0.4  setosa          5.4
 7         3.4          1.4         0.3  setosa          4.6
 8         3.4          1.5         0.2  setosa          5.0
 9         2.9          1.4         0.2  setosa          4.4
10         3.1          1.5         0.1  setosa          4.9
# ... with 140 more rows

[krlmlr]

@lionel-: Does this now belong in tidyselect?

[lionel-]

Yes. @hadley we could have everything_but(), or a but argument to everything()? Though that's not a frank improvement over the SO solution.

The issue is that everything() returns all positions without other semantic information, so we cannot reason over its output. Maybe it should return a tagged vector? Not sure how much that would complicate the implementation.

[romainfrancois]

Maybe that can be a new verb, e.g.

stash <- function(data, ...){
  nms <- names(data)
  all_vars <- vars_select( nms, everything() )
  sel_vars <- vars_select( nms, ... )
  
  selection <- c( setdiff( all_vars, sel_vars), sel_vars )
  select( data, one_of(selection) )
}
stash(iris, Sepal.Length)

Can be used to also move to first:

> ir <- as_tibble(iris)
> stash( ir, Sepal.Length )
# A tibble: 150 x 5
   Sepal.Width Petal.Length Petal.Width Species Sepal.Length
         <dbl>        <dbl>       <dbl>  <fctr>        <dbl>
 1         3.5          1.4         0.2  setosa          5.1
 2         3.0          1.4         0.2  setosa          4.9
 3         3.2          1.3         0.2  setosa          4.7
 4         3.1          1.5         0.2  setosa          4.6
 5         3.6          1.4         0.2  setosa          5.0
 6         3.9          1.7         0.4  setosa          5.4
 7         3.4          1.4         0.3  setosa          4.6
 8         3.4          1.5         0.2  setosa          5.0
 9         2.9          1.4         0.2  setosa          4.4
10         3.1          1.5         0.1  setosa          4.9
# ... with 140 more rows
> stash( ir, -Species )
# A tibble: 150 x 5
   Species Sepal.Length Sepal.Width Petal.Length Petal.Width
    <fctr>        <dbl>       <dbl>        <dbl>       <dbl>
 1  setosa          5.1         3.5          1.4         0.2
 2  setosa          4.9         3.0          1.4         0.2
 3  setosa          4.7         3.2          1.3         0.2
 4  setosa          4.6         3.1          1.5         0.2
 5  setosa          5.0         3.6          1.4         0.2
 6  setosa          5.4         3.9          1.7         0.4
 7  setosa          4.6         3.4          1.4         0.3
 8  setosa          5.0         3.4          1.5         0.2
 9  setosa          4.4         2.9          1.4         0.2
10  setosa          4.9         3.1          1.5         0.1
# ... with 140 more rows

[lionel-]

Another useful variant might be rotate(). In datasets with many columns, the variables are often sorted thematically.

cc @jennybc

[hadley]

This also works:

select(iris, -Sepal.Length, Sepal.Length)

i.e. select everything except Sepal.Length, then select Sepal.Length.

This also works:

dplyr::select(iris, -Sepal.Length, everything())

I don't think this is such a common operation that it needs it's own verb.

[jrosen48]

Is the logic of selecting a column to be first through select(iris, Species, everything()) that everything() works by selecting "everything else"?

If so, then could select(iris, everything(), Sepal.Length) be modified to (implicitly) work as "everything but"?

[lionel-]

No, it selects everything. It's like supplying 1, 1:10. The rendundant 1 is ignored and it still appears first in this case. But if you supply 1:10, 1, the last 1 is ignored.

[krlmlr]

This functionality seems to be easy enough to implement with existing functionality, and rare enough that it doesn't need its own verb. We could add an example to the documentation, either here or in tidyselect.

[romainfrancois]

Another take with some tidyeval :

library(purrr)
library(rlang)
#> 
#> Attaching package: 'rlang'
#> The following objects are masked from 'package:purrr':
#> 
#>     %@%, %||%, as_function, flatten, flatten_chr, flatten_dbl,
#>     flatten_int, flatten_lgl, invoke, list_along, modify, prepend,
#>     rep_along, splice
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

back <- function(data, ...){
  dots <- quos(...)
  ndots <- map(dots, function(q) expr(-!!q) )
  select( data, !!!ndots, !!!dots )
}
back(iris, Species) %>% head
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1          5.1         3.5          1.4         0.2  setosa
#> 2          4.9         3.0          1.4         0.2  setosa
#> 3          4.7         3.2          1.3         0.2  setosa
#> 4          4.6         3.1          1.5         0.2  setosa
#> 5          5.0         3.6          1.4         0.2  setosa
#> 6          5.4         3.9          1.7         0.4  setosa
back(iris, Species, starts_with("Petal")) %>% head
#>   Sepal.Length Sepal.Width Species Petal.Length Petal.Width
#> 1          5.1         3.5  setosa          1.4         0.2
#> 2          4.9         3.0  setosa          1.4         0.2
#> 3          4.7         3.2  setosa          1.3         0.2
#> 4          4.6         3.1  setosa          1.5         0.2
#> 5          5.0         3.6  setosa          1.4         0.2
#> 6          5.4         3.9  setosa          1.7         0.4

Created on 2018-04-23 by the reprex package (v0.2.0).