Merge gt elements or any other approach to create complex tables

Conferences & Events tables
1

Let's say I have this data:

df <- tibble(  
    col_a = paste("type",sample(letters[1:2],100,replac=T),sep="_"),
    col_b= paste("category",sample(letters[10:12],100,replac=T),sep="_"),
    col_c=runif(100, 5.0, 7.5),
    col_d=runif(100, 100.0, 105.5)
          )

I need to create a summary data table for the total sample as well as grouped by column_a, that looks more or less like this mockup:

gt_example
gt_example949×314 38.2 KB

Initially, I was going to create each piece separately and then merge it. I'm not sure whether this is the right approach, and I'm not sure if there's a way to merge the GT tables besides using some html tricks , which I prefer to avoid.

Here are the splitted gt-table elements:

     
table_type_a <- df %>% 
  filter(col_a=="type_a") %>% 
  group_by(col_b)  %>% 
  dplyr::summarise(col_c_sum=sum(col_c),
            col_d_mean=mean(col_d)) %>% 
  gt() %>% 
  tab_spanner(label="interesting numbers",
              columns =c(col_c_sum,col_d_mean)) %>% 
  fmt_number( columns =c(col_c_sum,col_d_mean),
              decimals = 1)

table_type_b <- df %>% 
  filter(col_a=="type_b") %>% 
  group_by(col_b)  %>% 
  dplyr::summarise(col_c_sum=sum(col_c),
                   col_d_mean=mean(col_d)) %>% 
  gt() %>% 
  tab_spanner(label="interesting numbers",
              columns =c(col_c_sum,col_d_mean)) %>% 
  fmt_number( columns =c(col_c_sum,col_d_mean),
              decimals = 1)

Thank you