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`juice()` should be able to return a 0 column data frame rather than abort() #298

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DavisVaughan opened this issue Mar 15, 2019 · 2 comments
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@DavisVaughan
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@DavisVaughan DavisVaughan commented Mar 15, 2019

I think it would be appropriate for juice() to return a 0 column tibble rather than abort when you try and use a selector that doesn't return any columns. This would match the behavior of dplyr::select() and would be useful for me in hardhat.

suppressPackageStartupMessages(library(recipes))

rec <- recipe(~ Sepal.Width, iris) %>%
  prep(iris)

juice(rec, all_predictors())
#> # A tibble: 150 x 1
#>    Sepal.Width
#>          <dbl>
#>  1         3.5
#>  2         3  
#>  3         3.2
#>  4         3.1
#>  5         3.6
#>  6         3.9
#>  7         3.4
#>  8         3.4
#>  9         2.9
#> 10         3.1
#> # … with 140 more rows

# should return tibble with 0 cols and 150 rows
juice(rec, all_outcomes())
#> Error: No variables or terms were selected.

If you look at dplyr::select(), a wrongly spelled column is an error, but a selector that returns 0 cols is fine.

dplyr::select(iris, "x")
#> Error: Unknown column `x`

dplyr::select(iris, dplyr::matches("x"))
#> data frame with 0 columns and 150 rows

juice() would still maintain the ability to error if someone did juice(rec, non_existant_column).

I think we can get this behavior by simply removing the abort from terms_select() here:
https://github.com/tidymodels/recipes/blob/master/R/selections.R#L196

That is a pretty commonly used function though, so maybe we'd want a version that is strict (the current behavior), and a version that isn't as strict (the suggested behavior).

@alexpghayes
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@alexpghayes alexpghayes commented Mar 31, 2019

Would you mind describing how this helps out in hardhat()? I think returning a 0-column tibble is dangerous and the kind of thing you want to error out on as early as possible to make debugging your pipeline as easy as possible.

@topepo
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@topepo topepo commented Jul 22, 2019

Example:

library(recipes)
#> Loading required package: 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
#> 
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#> 
#>     step
recipe(~ ., data = iris) %>% prep() %>% juice(all_outcomes())
#> # A tibble: 0 x 0

Created on 2019-07-22 by the reprex package (v0.2.1)

For hardhat... before:

hardhat::mold(recipes::recipe(~ ., iris), iris)
#> No variables or terms were selected.
sessionInfo(package = "recipes")
#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS High Sierra 10.13.6
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> character(0)
#> 
#> other attached packages:
#> [1] recipes_0.1.6
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.1         pillar_1.4.2       compiler_3.6.0    
#>  [4] gower_0.2.0        highr_0.8          methods_3.6.0     
#>  [7] class_7.3-15       utils_3.6.0        tools_3.6.0       
#> [10] grDevices_3.6.0    zeallot_0.1.0      rpart_4.1-15      
#> [13] digest_0.6.20      ipred_0.9-8        lubridate_1.7.4   
#> [16] evaluate_0.14      tibble_2.1.3       lattice_0.20-38   
#> [19] pkgconfig_2.0.2    rlang_0.4.0.9000   Matrix_1.2-17     
#> [22] yaml_2.2.0         prodlim_2018.04.18 xfun_0.8          
#> [25] withr_2.1.2        stringr_1.4.0      dplyr_0.8.3       
#> [28] knitr_1.23         generics_0.0.2     vctrs_0.2.0.9000  
#> [31] graphics_3.6.0     datasets_3.6.0     stats_3.6.0       
#> [34] nnet_7.3-12        grid_3.6.0         tidyselect_0.2.5  
#> [37] glue_1.3.1         base_3.6.0         R6_2.4.0          
#> [40] survival_2.44-1.1  rmarkdown_1.14     lava_1.6.5        
#> [43] tidyr_0.8.3        purrr_0.3.2        magrittr_1.5      
#> [46] splines_3.6.0      backports_1.1.4    htmltools_0.3.6   
#> [49] MASS_7.3-51.4      assertthat_0.2.1   hardhat_0.0.0.9000
#> [52] timeDate_3043.102  stringi_1.4.3      crayon_1.3.4

Created on 2019-07-22 by the reprex package (v0.2.1)

and after

hardhat::mold(recipes::recipe(~ ., iris), iris)
#> $predictors
#> # A tibble: 150 x 5
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#>           <dbl>       <dbl>        <dbl>       <dbl> <fct>  
#>  1          5.1         3.5          1.4         0.2 setosa 
#>  2          4.9         3            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           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           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
#> 
#> $outcomes
#> # A tibble: 0 x 0
#> 
#> $blueprint
#> Recipe blueprint: 
#>  
#> # Predictors: 5 
#>   # Outcomes: 0 
#>    Intercept: FALSE 
#> 
#> $extras
#> $extras$roles
#> NULL
sessionInfo(package = "recipes")
#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS High Sierra 10.13.6
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> character(0)
#> 
#> other attached packages:
#> [1] recipes_0.1.6.9000
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.1         pillar_1.4.2       compiler_3.6.0    
#>  [4] gower_0.2.0        highr_0.8          methods_3.6.0     
#>  [7] class_7.3-15       utils_3.6.0        tools_3.6.0       
#> [10] grDevices_3.6.0    zeallot_0.1.0      rpart_4.1-15      
#> [13] digest_0.6.20      ipred_0.9-8        lubridate_1.7.4   
#> [16] evaluate_0.14      tibble_2.1.3       lattice_0.20-38   
#> [19] pkgconfig_2.0.2    rlang_0.4.0.9000   Matrix_1.2-17     
#> [22] cli_1.1.0          yaml_2.2.0         prodlim_2018.04.18
#> [25] xfun_0.8           withr_2.1.2        stringr_1.4.0     
#> [28] dplyr_0.8.3        knitr_1.23         generics_0.0.2    
#> [31] vctrs_0.2.0.9000   graphics_3.6.0     datasets_3.6.0    
#> [34] stats_3.6.0        nnet_7.3-12        grid_3.6.0        
#> [37] tidyselect_0.2.5   glue_1.3.1         base_3.6.0        
#> [40] R6_2.4.0           fansi_0.4.0        survival_2.44-1.1 
#> [43] rmarkdown_1.14     lava_1.6.5         tidyr_0.8.3       
#> [46] purrr_0.3.2        magrittr_1.5       splines_3.6.0     
#> [49] backports_1.1.4    htmltools_0.3.6    MASS_7.3-51.4     
#> [52] assertthat_0.2.1   hardhat_0.0.0.9000 timeDate_3043.102 
#> [55] utf8_1.1.4         stringi_1.4.3      crayon_1.3.4

Created on 2019-07-22 by the reprex package (v0.2.1)

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