Applying custom formatting to pivot table

Hello,

I have the following data which is just the diamond dataset with an additional Qualify column. I need custom formatting to happen on the pivot table based on the Qualify column.

library(tidyverse)
library(radiant.data)
#> Loading required package: magrittr
#> 
#> Attaching package: 'magrittr'
#> The following object is masked from 'package:purrr':
#> 
#>     set_names
#> The following object is masked from 'package:tidyr':
#> 
#>     extract
#> Loading required package: lubridate
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
#> 
#> Attaching package: 'radiant.data'
#> The following objects are masked from 'package:lubridate':
#> 
#>     month, wday
#> The following object is masked from 'package:forcats':
#> 
#>     as_factor
#> The following objects are masked from 'package:purrr':
#> 
#>     is_double, is_empty, is_numeric
#> The following object is masked from 'package:ggplot2':
#> 
#>     diamonds
#> The following object is masked from 'package:base':
#> 
#>     date
library(DT)

df_diamonds <- diamonds %>% 
  mutate(Qualify = sample(c(0:1), replace = TRUE, size = nrow(diamonds)))

df_diamonds
#> # A tibble: 3,000 x 12
#>    price carat clarity cut   color depth table     x     y     z date      
#>    <int> <dbl> <fct>   <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <date>    
#>  1   580  0.32 VS1     Ideal H      61    56    4.43  4.45  2.71 2012-02-26
#>  2   650  0.34 SI1     Very~ G      63.4  57    4.45  4.42  2.81 2012-02-26
#>  3   630  0.3  VS2     Very~ G      63.1  58    4.27  4.23  2.68 2012-02-26
#>  4   706  0.35 VVS2    Ideal H      59.2  56    4.6   4.65  2.74 2012-02-26
#>  5  1080  0.4  VS2     Prem~ F      62.6  58    4.72  4.68  2.94 2012-02-26
#>  6  3082  0.6  VVS1    Ideal E      62.5  53.7  5.35  5.43  3.38 2012-02-26
#>  7  3328  0.88 SI1     Ideal I      61.7  56    6.14  6.18  3.8  2012-02-26
#>  8  4229  0.93 SI1     Prem~ E      61.4  57    6.34  6.23  3.86 2012-02-26
#>  9  1895  0.51 VVS2    Very~ G      63.4  57    5.09  5.06  3.22 2012-02-26
#> 10  3546  1.01 SI2     Good  E      63.9  58    6.31  6.37  4.05 2012-02-26
#> # ... with 2,990 more rows, and 1 more variable: Qualify <int>

tab <- pivotr(df_diamonds, cvars = c("cut","color","carat"), nvar = "price", fun = "n_obs") %>% 
  dtab(format="color_bar")
#tab

Created on 2020-09-27 by the reprex package (v0.3.0)

Currently the table looks like this:

What I want to happen is that say 1 of 5 values in very good x d x 0.3 has 0 in Qualify it needs to grey out that number in the pivot. If at least one of the values in the aggregate for the pivot contain 0 then it needs to grey it out (not delete it as I still need the number for reference).

Can anyone assist?

Any help on this? :slight_smile:

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