`view_df()`: Show variables with complete NA's.

[brianmsm]

Is there any way or possibility to request that the output also shows variables containing full NA's? I thought that adding show.na = TRUE would do it, but it seems that it is only to add a column to report the presence of missing values.

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
library(sjPlot)

df <- tibble(
  var1 = c(rep(1, 5), rep(2, 3), rep(3, 10)),
  var2 = c(rep(1, 3), rep(2, 5), rep(3, 8), rep(NA_integer_, 2)),
  var3 = NA_integer_
)

df <- df %>%
  sjlabelled::set_labels(var1, var2, var3,
                         labels = c("Option 1" = 1,
                                    "Option 2" = 2,
                                    "Option 3" = 3))  %>%
  sjlabelled::var_labels(var1 = "Variable 1", 
                         var2 = "Variable 2",
                         var3 = "Variable 3")


sjPlot::view_df(df, show.type = TRUE, show.na = TRUE)
#> Following 1 variables have only missing values and are not shown:
#> var3 [3]

Data frame: df

ID	Name	Type	Label	missings	Values	Value Labels
1	var1	numeric	Variable 1	0 (0.00%)	1 2 3	Option 1 Option 2 Option 3
2	var2	numeric	Variable 2	2 (11.11%)	1 2 3	Option 1 Option 2 Option 3

^{Created on 2022-06-04 by the reprex package (v2.0.1)}

[strengejacke]

Currently, this is not possible.