vfold_cv crashing/freezing the console about rsample HOT 12 CLOSED

Hello @godscloset ! That is unfortunate, it should definitely work! Can you run the following code for me and show us the results? I wanna make sure you are using up to date versions of the packages

library(tidymodels)

sessionInfo()

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Hey! I think you forgot to attach the screenshot :)

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Oh I see what happened. I tried to reply via email and not through github.

-J

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Hi!
Another revelation: it seems like when I try to 'view' the created vfold object is when everything breaks down. Weirdly, this was working before but now causes the crash-- I don't know if this helps.
-Jacob

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when you say view do you mean using the View() function, or having the object printed to the console?

View() doesn't handle non-standard data.frames very well and is not recommended to be used on tidymodels objects.

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To be clear, this is not a tidymodels problem, but a RStudio IDE issue. RStudio is slow/crashes when trying to View() a data.frame with list columns rstudio/rstudio#2039.

We understand the frustration, which is why we generally discourage working with list-columns directly. The {tune} package has collect_*() functions that allow you to extract wanted information to a non-list-column-data.frame.

If you still want to see what happens with your data while working with list columns you can unselect them before using View()

folds %>%
  select(!where(is.list)) %>%
  View()

Another thing you could do is poke around with str(folds, max.level = 1) while slowly increasing max.level to avoid massive printing. I personally also enjoy using glimpse() for data.frames.

{recipes} objects themselves are not that great to look at for the user, as they contain quite a bit of information. If you were to investigate I would encourage the use of tidy() as an extracting function, and turn the data into a viewable format

library(tidymodels)
library(modeldata)
data(meats)

norm_rec <- 
  recipe(water + fat + protein ~ ., data = meats) %>%
  step_normalize(all_predictors()) 

set.seed(57343)
folds <- vfold_cv(meats, repeats = 10)

folds <- 
  folds %>%
  mutate(recipes = map(splits, prepper, recipe = norm_rec))

folds %>%
  mutate(recipes = map(splits, prepper, recipe = norm_rec)) %>%
  mutate(tidy = map(recipes, tidy, 1)) %>%
  select(-splits, -recipes) %>%
  rename(repeat_id = id) %>%
  unnest(tidy)
#> # A tibble: 20,000 × 6
#>    repeat_id id2    terms statistic value id             
#>    <chr>     <chr>  <chr> <chr>     <dbl> <chr>          
#>  1 Repeat01  Fold01 x_001 mean       2.82 normalize_CiSI9
#>  2 Repeat01  Fold01 x_002 mean       2.82 normalize_CiSI9
#>  3 Repeat01  Fold01 x_003 mean       2.83 normalize_CiSI9
#>  4 Repeat01  Fold01 x_004 mean       2.83 normalize_CiSI9
#>  5 Repeat01  Fold01 x_005 mean       2.83 normalize_CiSI9
#>  6 Repeat01  Fold01 x_006 mean       2.84 normalize_CiSI9
#>  7 Repeat01  Fold01 x_007 mean       2.84 normalize_CiSI9
#>  8 Repeat01  Fold01 x_008 mean       2.84 normalize_CiSI9
#>  9 Repeat01  Fold01 x_009 mean       2.85 normalize_CiSI9
#> 10 Repeat01  Fold01 x_010 mean       2.85 normalize_CiSI9
#> # ℹ 19,990 more rows

May I act what information you were hoping to see when calling View() on folds in the example above?

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Thank you, this is very useful.

I mostly would like to be able to view lists in RStudio, such as those generated by rsample for bootstrapping and after nesting. I guess my problem is that I still have a hard time wrapping my head around exactly what information is at what "level" and what the different subparts contain.

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Thanks for the discussion! I'm going to close as this is not an rsample issue.

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This issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.

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