Printing more rows than default max has unexpected behavior #734
Description
If I have a summary which is long, I sometimes want to add print(n=bignumber) to the end to get all of the summary to print but this doesn't behave as I would expect. Below, I would expect Example 1 and Example 2 to print the same thing but they don't. This is more important when I have even more rows as is true in example 3 and 4. It seems n is being ignored altogether
Here's a reprex to show:
library(skimr)
#> Warning: package 'skimr' was built under R version 4.2.3
library(tidyverse)
sum_cut <- diamonds %>% group_by(cut) %>% skim(carat) %>% yank("numeric")
sum_cut_color <- diamonds %>% group_by(cut, color) %>% skim(carat) %>% yank("numeric")
sum_cut #example 1Variable type: numeric
| skim_variable | cut | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|
| carat | Fair | 0 | 1 | 1.05 | 0.52 | 0.22 | 0.70 | 1.00 | 1.20 | 5.01 | ▇▂▁▁▁ |
| carat | Good | 0 | 1 | 0.85 | 0.45 | 0.23 | 0.50 | 0.82 | 1.01 | 3.01 | ▇▆▂▁▁ |
| carat | Very Good | 0 | 1 | 0.81 | 0.46 | 0.20 | 0.41 | 0.71 | 1.02 | 4.00 | ▇▃▁▁▁ |
| carat | Premium | 0 | 1 | 0.89 | 0.52 | 0.20 | 0.41 | 0.86 | 1.20 | 4.01 | ▇▆▁▁▁ |
| carat | Ideal | 0 | 1 | 0.70 | 0.43 | 0.20 | 0.35 | 0.54 | 1.01 | 3.50 | ▇▂▁▁▁ |
sum_cut %>% print(n=50) # example 2
#>
#> ── Variable type: numeric ──────────────────────────────────────────────────────
#> skim_variable cut n_mis…¹ compl…² mean sd p0 p25 p50 p75 p100 hist
#> 1 carat Fair 0 1 1.05 0.516 0.22 0.7 1 1.2 5.01 ▇▂▁…
#> 2 carat Good 0 1 0.849 0.454 0.23 0.5 0.82 1.01 3.01 ▇▆▂…
#> 3 carat Very … 0 1 0.806 0.459 0.2 0.41 0.71 1.02 4 ▇▃▁…
#> 4 carat Premi… 0 1 0.892 0.515 0.2 0.41 0.86 1.2 4.01 ▇▆▁…
#> 5 carat Ideal 0 1 0.703 0.433 0.2 0.35 0.54 1.01 3.5 ▇▂▁…
#> # … with abbreviated variable names ¹n_missing, ²complete_rate
sum_cut_color # example 3Variable type: numeric
| skim_variable | cut | color | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| carat | Fair | D | 0 | 1 | 0.92 | 0.41 | 0.25 | 0.70 | 0.90 | 1.01 | 3.40 | ▆▇▁▁▁ |
| carat | Fair | E | 0 | 1 | 0.86 | 0.36 | 0.22 | 0.55 | 0.90 | 1.01 | 2.04 | ▇▇▇▂▁ |
| carat | Fair | F | 0 | 1 | 0.90 | 0.42 | 0.25 | 0.60 | 0.90 | 1.01 | 2.58 | ▇▇▂▁▁ |
| carat | Fair | G | 0 | 1 | 1.02 | 0.49 | 0.23 | 0.70 | 0.98 | 1.07 | 2.60 | ▅▇▂▂▁ |
| carat | Fair | H | 0 | 1 | 1.22 | 0.55 | 0.33 | 0.90 | 1.01 | 1.51 | 4.13 | ▇▃▂▁▁ |
| carat | Fair | I | 0 | 1 | 1.20 | 0.52 | 0.41 | 0.88 | 1.01 | 1.50 | 3.02 | ▇▇▃▂▁ |
| carat | Fair | J | 0 | 1 | 1.34 | 0.73 | 0.30 | 0.90 | 1.03 | 1.69 | 5.01 | ▇▃▁▁▁ |
| carat | Good | D | 0 | 1 | 0.74 | 0.36 | 0.23 | 0.42 | 0.70 | 1.00 | 2.04 | ▇▅▅▁▁ |
| carat | Good | E | 0 | 1 | 0.75 | 0.38 | 0.23 | 0.41 | 0.70 | 1.00 | 3.00 | ▇▅▁▁▁ |
| carat | Good | F | 0 | 1 | 0.78 | 0.37 | 0.23 | 0.49 | 0.71 | 1.01 | 2.67 | ▇▆▁▁▁ |
| carat | Good | G | 0 | 1 | 0.85 | 0.43 | 0.23 | 0.50 | 0.90 | 1.01 | 2.80 | ▇▇▂▁▁ |
| carat | Good | H | 0 | 1 | 0.91 | 0.50 | 0.25 | 0.51 | 0.90 | 1.09 | 3.01 | ▇▇▂▁▁ |
| carat | Good | I | 0 | 1 | 1.06 | 0.58 | 0.30 | 0.70 | 1.00 | 1.50 | 3.01 | ▇▆▃▂▁ |
| carat | Good | J | 0 | 1 | 1.10 | 0.54 | 0.28 | 0.71 | 1.02 | 1.50 | 3.00 | ▇▇▅▂▁ |
| carat | Very Good | D | 0 | 1 | 0.70 | 0.37 | 0.23 | 0.40 | 0.61 | 1.00 | 2.58 | ▇▅▁▁▁ |
| carat | Very Good | E | 0 | 1 | 0.68 | 0.38 | 0.20 | 0.37 | 0.57 | 0.94 | 2.51 | ▇▆▁▁▁ |
| carat | Very Good | F | 0 | 1 | 0.74 | 0.39 | 0.23 | 0.40 | 0.70 | 1.01 | 2.48 | ▇▇▂▁▁ |
| carat | Very Good | G | 0 | 1 | 0.77 | 0.42 | 0.23 | 0.40 | 0.70 | 1.02 | 2.52 | ▇▆▂▁▁ |
| carat | Very Good | H | 0 | 1 | 0.92 | 0.50 | 0.23 | 0.47 | 0.90 | 1.20 | 3.00 | ▇▇▂▁▁ |
| carat | Very Good | I | 0 | 1 | 1.05 | 0.55 | 0.24 | 0.70 | 1.00 | 1.50 | 4.00 | ▇▆▂▁▁ |
| carat | Very Good | J | 0 | 1 | 1.13 | 0.56 | 0.24 | 0.71 | 1.06 | 1.51 | 2.74 | ▇▇▆▃▁ |
| carat | Premium | D | 0 | 1 | 0.72 | 0.40 | 0.20 | 0.40 | 0.58 | 1.01 | 2.57 | ▇▅▂▁▁ |
| carat | Premium | E | 0 | 1 | 0.72 | 0.41 | 0.20 | 0.38 | 0.58 | 1.00 | 3.05 | ▇▃▁▁▁ |
| carat | Premium | F | 0 | 1 | 0.83 | 0.42 | 0.20 | 0.43 | 0.76 | 1.04 | 3.01 | ▇▆▂▁▁ |
| carat | Premium | G | 0 | 1 | 0.84 | 0.48 | 0.23 | 0.40 | 0.76 | 1.12 | 3.01 | ▇▆▂▁▁ |
| carat | Premium | H | 0 | 1 | 1.02 | 0.54 | 0.23 | 0.51 | 1.01 | 1.30 | 3.24 | ▇▇▃▁▁ |
| carat | Premium | I | 0 | 1 | 1.14 | 0.61 | 0.23 | 0.59 | 1.14 | 1.54 | 4.01 | ▇▇▃▁▁ |
| carat | Premium | J | 0 | 1 | 1.29 | 0.61 | 0.30 | 0.81 | 1.25 | 1.70 | 4.01 | ▇▇▃▁▁ |
| carat | Ideal | D | 0 | 1 | 0.57 | 0.30 | 0.20 | 0.33 | 0.50 | 0.71 | 2.75 | ▇▂▁▁▁ |
| carat | Ideal | E | 0 | 1 | 0.58 | 0.31 | 0.20 | 0.33 | 0.50 | 0.72 | 2.28 | ▇▂▁▁▁ |
| carat | Ideal | F | 0 | 1 | 0.66 | 0.37 | 0.23 | 0.35 | 0.53 | 0.90 | 2.45 | ▇▃▁▁▁ |
| carat | Ideal | G | 0 | 1 | 0.70 | 0.41 | 0.23 | 0.34 | 0.54 | 1.03 | 2.54 | ▇▃▂▁▁ |
| carat | Ideal | H | 0 | 1 | 0.80 | 0.49 | 0.23 | 0.36 | 0.70 | 1.11 | 3.50 | ▇▅▁▁▁ |
| carat | Ideal | I | 0 | 1 | 0.91 | 0.55 | 0.23 | 0.41 | 0.74 | 1.22 | 3.22 | ▇▃▂▁▁ |
| carat | Ideal | J | 0 | 1 | 1.06 | 0.58 | 0.23 | 0.54 | 1.03 | 1.41 | 3.01 | ▇▆▃▂▁ |
sum_cut_color %>% print(n=50) # example 4
#>
#> ── Variable type: numeric ──────────────────────────────────────────────────────
#> skim_…¹ cut color n_mis…² compl…³ mean sd p0 p25 p50 p75 p100 hist
#> 1 carat Fa… D 0 1 0.920 0.405 0.25 0.7 0.9 1.01 3.4 ▆▇▁…
#> 2 carat Fa… E 0 1 0.857 0.365 0.22 0.552 0.9 1.01 2.04 ▇▇▇…
#> 3 carat Fa… F 0 1 0.905 0.419 0.25 0.6 0.9 1.01 2.58 ▇▇▂…
#> 4 carat Fa… G 0 1 1.02 0.493 0.23 0.7 0.98 1.07 2.6 ▅▇▂…
#> 5 carat Fa… H 0 1 1.22 0.548 0.33 0.9 1.01 1.51 4.13 ▇▃▂…
#> 6 carat Fa… I 0 1 1.20 0.522 0.41 0.885 1.01 1.50 3.02 ▇▇▃…
#> 7 carat Fa… J 0 1 1.34 0.734 0.3 0.905 1.03 1.68 5.01 ▇▃▁…
#> 8 carat Go… D 0 1 0.745 0.363 0.23 0.42 0.7 1 2.04 ▇▅▅…
#> 9 carat Go… E 0 1 0.745 0.381 0.23 0.41 0.7 1 3 ▇▅▁…
#> 10 carat Go… F 0 1 0.776 0.370 0.23 0.49 0.71 1.01 2.67 ▇▆▁…
#> 11 carat Go… G 0 1 0.851 0.433 0.23 0.5 0.9 1.01 2.8 ▇▇▂…
#> 12 carat Go… H 0 1 0.915 0.498 0.25 0.51 0.9 1.09 3.01 ▇▇▂…
#> 13 carat Go… I 0 1 1.06 0.576 0.3 0.7 1 1.5 3.01 ▇▆▃…
#> 14 carat Go… J 0 1 1.10 0.537 0.28 0.71 1.02 1.5 3 ▇▇▅…
#> 15 carat Ve… D 0 1 0.696 0.369 0.23 0.4 0.61 1 2.58 ▇▅▁…
#> 16 carat Ve… E 0 1 0.676 0.378 0.2 0.37 0.57 0.94 2.51 ▇▆▁…
#> 17 carat Ve… F 0 1 0.741 0.389 0.23 0.4 0.7 1.01 2.48 ▇▇▂…
#> 18 carat Ve… G 0 1 0.767 0.418 0.23 0.4 0.7 1.02 2.52 ▇▆▂…
#> 19 carat Ve… H 0 1 0.916 0.503 0.23 0.467 0.9 1.2 3 ▇▇▂…
#> 20 carat Ve… I 0 1 1.05 0.552 0.24 0.7 1.00 1.5 4 ▇▆▂…
#> 21 carat Ve… J 0 1 1.13 0.556 0.24 0.71 1.06 1.51 2.74 ▇▇▆…
#> 22 carat Pr… D 0 1 0.722 0.397 0.2 0.4 0.58 1.01 2.57 ▇▅▂…
#> 23 carat Pr… E 0 1 0.718 0.410 0.2 0.38 0.58 1 3.05 ▇▃▁…
#> 24 carat Pr… F 0 1 0.827 0.420 0.2 0.43 0.76 1.04 3.01 ▇▆▂…
#> 25 carat Pr… G 0 1 0.841 0.480 0.23 0.4 0.755 1.12 3.01 ▇▆▂…
#> 26 carat Pr… H 0 1 1.02 0.544 0.23 0.51 1.01 1.3 3.24 ▇▇▃…
#> 27 carat Pr… I 0 1 1.14 0.614 0.23 0.59 1.14 1.54 4.01 ▇▇▃…
#> 28 carat Pr… J 0 1 1.29 0.614 0.3 0.81 1.25 1.7 4.01 ▇▇▃…
#> 29 carat Id… D 0 1 0.566 0.299 0.2 0.33 0.5 0.71 2.75 ▇▂▁…
#> 30 carat Id… E 0 1 0.578 0.313 0.2 0.33 0.5 0.72 2.28 ▇▂▁…
#> 31 carat Id… F 0 1 0.656 0.375 0.23 0.35 0.53 0.9 2.45 ▇▃▁…
#> 32 carat Id… G 0 1 0.701 0.411 0.23 0.34 0.54 1.03 2.54 ▇▃▂…
#> 33 carat Id… H 0 1 0.800 0.487 0.23 0.36 0.7 1.11 3.5 ▇▅▁…
#> 34 carat Id… I 0 1 0.913 0.554 0.23 0.41 0.74 1.22 3.22 ▇▃▂…
#> 35 carat Id… J 0 1 1.06 0.582 0.23 0.54 1.03 1.41 3.01 ▇▆▃…
#> # … with abbreviated variable names ¹skim_variable, ²n_missing, ³complete_rateCreated on 2023-04-03 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.2.2 (2022-10-31 ucrt)
#> os Windows 10 x64 (build 19045)
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate English_United States.utf8
#> ctype English_United States.utf8
#> tz America/New_York
#> date 2023-04-03
#> pandoc 2.19.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#>
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#>
#> ──────────────────────────────────────────────────────────────────────────────