Use dplyr 1.0.0 rowwise to add summary rows

transpose-summary-row.R

library(ggplot2)
library(tidyr)
library(dplyr, warn.conflicts = FALSE)

diamonds_sum <- diamonds %>%
  mutate(across(cut, as.character)) %>%
  group_by(cut) %>%
  summarise(across(price, sum), across(carat, n_distinct), n = n())

diamonds_sum
#> # A tibble: 5 x 4
#>   cut          price carat     n
#> * <chr>        <int> <int> <int>
#> 1 Fair       7017600   185  1610
#> 2 Good      19275009   199  4906
#> 3 Ideal     74513487   232 21551
#> 4 Premium   63221498   251 13791
#> 5 Very Good 48107623   231 12082

transpose_df <- function(x, col, name) {
  x %>%
    pivot_longer(-{{ col }}, names_to = name) %>%
    pivot_wider(names_from = {{ col }})
}

diamonds_sum %>%
  transpose_df(cut, "feature") %>%
  rowwise(feature) %>%
  mutate(total = sum(c_across())) %>%
  transpose_df(feature, "cut")
#> # A tibble: 6 x 4
#>   cut           price carat     n
#>   <chr>         <int> <int> <int>
#> 1 Fair        7017600   185  1610
#> 2 Good       19275009   199  4906
#> 3 Ideal      74513487   232 21551
#> 4 Premium    63221498   251 13791
#> 5 Very Good  48107623   231 12082
#> 6 total     212135217  1098 53940