Issue with weighted percentage in flat_table()

[realrbird]

library(tidyverse)
library(sjmisc)

df <- mtcars %>%
  mutate(cyl = as.factor(cyl), gear = as.factor(gear)) %>%
  select(cyl, gear, mpg) %>%
  na.omit() %>%
  as_tibble()

# Using sjmisc
flat_table(df, cyl, gear, weights = mpg, margin = 'col', digits = 9)
#>     gear         3         4         5
#> cyl                                   
#> 4         9.053498 73.129252 52.336449
#> 6        16.460905 26.870748 18.691589
#> 8        74.485597  0.000000 28.971963

# using dplyr
count(df, cyl, gear, .drop = FALSE, wt = mpg) %>%
  group_by(gear) %>%
  mutate(n = (n/sum(n)) * 100) %>%
  pivot_wider(names_from = gear, values_from = n) %>%
  as.data.frame()
#>   cyl         3        4        5
#> 1   4  8.899007 73.16576 52.75959
#> 2   6 16.349338 26.83424 18.42844
#> 3   8 74.751656  0.00000 28.81197

# WORKS FINE WITHOUT WEIGHTS
flat_table(df, cyl, gear, margin = 'col', digits = 9)
#>     gear         3         4         5
#> cyl                                   
#> 4         6.666667 66.666667 40.000000
#> 6        13.333333 33.333333 20.000000
#> 8        80.000000  0.000000 40.000000

count(df, cyl, gear, .drop = FALSE) %>%
  group_by(gear) %>%
  mutate(n = (n/sum(n)) * 100) %>%
  pivot_wider(names_from = gear, values_from = n) %>%
  as.data.frame()
#>   cyl         3        4  5
#> 1   4  6.666667 66.66667 40
#> 2   6 13.333333 33.33333 20
#> 3   8 80.000000  0.00000 40

^{Created on 2022-05-12 by the reprex package (v2.0.1)}