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Error in unsplit() with tibbles

6 messages · Marc Schwartz, Peter Dalgaard, Mario Annau

Original
Mario Annau
# 
Hello,

using the `unsplit()` function with tibbles currently leads to the
following error:
Error: Must subset rows with a valid subscript vector.
? Logical subscripts must match the size of the indexed input.
x Input has size 15 but subscript `rep(NA, len)` has size 32.
Run `rlang::last_error()` to see where the error occurred.

Tibble seems to (rightly) complain, that a logical vector has been used for
subsetting which does not have the same length as the data.frame (rows).
Since `NA` is a logical value, the subset should be changed to
`NA_integer_` in `unsplit()`:
function (value, f, drop = FALSE)
{
    len <- length(if (is.list(f)) f[[1L]] else f)
    if (is.data.frame(value[[1L]])) {
        x <- value[[1L]][rep(*NA_integer_*, len), , drop = FALSE]
        rownames(x) <- unsplit(lapply(value, rownames), f, drop = drop)
    }
    else x <- value[[1L]][rep(NA, len)]
    split(x, f, drop = drop) <- value
    x
}

Cheers,
Mario
Marc Schwartz
# 
Hi,

Perhaps I am missing something, but if you are using objects, like tibbles, that are intended to be part of another environment, in this case the tidyverse, why would you not use functions to manipulate these objects that were specifically created in the other environment?

I don't use the tidyverse, but it seems to me that to expect base R functions to work with objects not created in base R, is problematic, even though, perhaps by coincidence, they may work without adverse effects, as appears to be the case with split(). 

In other words, you should not, in reality, have had an a priori expectation that split() would work with a tibble either.

Rather than modifying the base R functions, like unsplit(), as you are suggesting, to be compatible with these third party objects, the burden should either be on you to use relevant tidyverse functions, or on the authors of the tidyverse to provide relevant class methods to provide that functionality.

Regards,

Marc Schwartz
Peter Dalgaard
# 
Yes. Nevermind tibbles, the [rep(NA, len),] construction only happens to work because len will always be >= the number of rows in  value[[1L]], witness
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[1] NA NA NA NA NA NA NA NA NA NA
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

-pd

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Peter Dalgaard
    

    

      
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I get the sentiment, but this is really just bad coding (on my own part, I suspect), so we might as well just fix it...

-pd

            

      
      
      
    

        

      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Mario Annau
    

    

      
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Cool - thank you Peter!

@Marc: This is really not a tidyverse vs base-R debate and I personally
think that they should both work together for most parts. The common
environment is still R. But just to give you the full picture I also filed
a bug for tibbles (https://github.com/tidyverse/tibble/issues/829). With
these two fixes I think that split/unsplit would work for tibbles and users
(like me) just don't have to care in which "environments" they are working
in.

Cheers,
Mario

        
On Sat, 21 Nov 2020 at 17:54, Peter Dalgaard <pdalgd at gmail.com> wrote:

        

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Marc Schwartz
    

    

      
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Hi,

Peter, thanks for the clarification.


Mario, I was not looking to debate the pros and cons of each environment, simply to point out that expecting mutually compatible functionality is not generalizable, especially when third party authors can make structural changes to their objects over time, that can then make them incompatible with base R functions, even if they may be today.

That is a key basis for third party packages offering specific class methods, whether S3 or S4, for object classes that are unique to their packages. That approach provides the obvious level of transparency.

For the tidyverse folks to offer a variant of split() and unsplit() that have specific methods for tibbles would seem entirely reasonable, presuming that they don't have a philosophical barrier to doing so, in deference to other approaches that do conform to their preferred function syntax.

Regards,

Marc