trouble with the function function

Hi. I'm attempting to sort marital groups in descending order of income using a stacked barchart. I have a solution, but am having trouble wrapping it into a function. When I attempt to do so, I end up with NAs in the marital column. My goal is to get the same plot output as shown below, but using a function to wrap this chunk of code (to make it more general). Thanks.

data_sorted <- group_income %>%
filter(rincome == "$25000 or more") %>%
arrange(desc(percent))
 
group_income <- group_income %>%
mutate(marital = factor(marital, levels=data_sorted %>% pull(marital)))

Below is the full example:

suppressWarnings({
library(tidyverse)
library(viridis)})
#> Loading required package: viridisLite

# reverse code income
gss_cat2 <- gss_cat %>% # gss_cat loads with tidyverse
  mutate(rincome = fct_rev(rincome))

# filter non-income responses
"%!in%" <- Negate("%in%")

group_income <- gss_cat2 %>% 
  filter(rincome %!in% c("No answer", "Don't know", "Refused", "Not applicable")) %>%
  group_by(marital, rincome) %>% 
  summarize(n = n()) %>% 
  mutate(percent = round((n / sum(n)*100), 2))
#> `summarise()` has grouped output by 'marital'. You can override using the `.groups` argument.

# sort marital by income
# using one of the responses here: https://community.rstudio.com/t/r-ggplot2-reorder-stacked-plot/23912/5
data_sorted <- group_income %>%
  filter(rincome == "$25000 or more") %>%
  arrange(desc(percent))

# recode marital based on income sorting
group_income <- group_income %>%
  mutate(marital = factor(marital, levels=data_sorted %>% pull(marital)))

# the point of this is to plot in descending order using a stacked bar chart
group_income %>% 
  filter(!is.na(marital)) %>% 
  ggplot(aes(x = percent, y = fct_rev(marital), fill = rincome)) +
  geom_col(width = 0.4) +
  scale_fill_viridis(discrete = TRUE) +
  theme_minimal()


# what I'd like to do is wrap the "sort marital by income," and "recode marital" 
# chunks into a function, ideally so that the whole thing can be piped together
sort_descending <- function(df, filter_var, filter_lab, sort_var) {
  
  df_sorted <- df %>%
    filter({{filter_var}} == filter_lab) %>%
    arrange(desc(percent))
  
  df <- df %>%
    mutate(!!sort_var := factor(!!sort_var, levels=df_sorted %>% pull({{sort_var}})))
  
  df
}

# so far, when I do so, I get NAs in the marital column
sort_descending(group_income, rincome, "$25000 or more", "marital")
#> # A tibble: 62 x 4
#> # Groups:   marital [1]
#>    marital rincome            n percent
#>    <fct>   <fct>          <int>   <dbl>
#>  1 <NA>    $10000 - 14999     1   50   
#>  2 <NA>    $20000 - 24999     1   50   
#>  3 <NA>    Lt $1000         124    3.39
#>  4 <NA>    $1000 to 2999    196    5.35
#>  5 <NA>    $3000 to 3999    125    3.41
#>  6 <NA>    $4000 to 4999     95    2.59
#>  7 <NA>    $5000 to 5999     92    2.51
#>  8 <NA>    $6000 to 6999     82    2.24
#>  9 <NA>    $7000 to 7999     85    2.32
#> 10 <NA>    $8000 to 9999    135    3.69
#> # ... with 52 more rows

Created on 2021-08-18 by the reprex package (v2.0.0)

As an aside, I don't know how to get the plot to print. Any guidance with that would also be useful.

Hi. Replying to my own post in hopes of getting more eyes on it.

sort_descending <- function(df, filter_var, filter_lab, sort_var) {

  df_sorted <- df %>%
    filter({{filter_var}} == filter_lab) %>%
    arrange(desc(percent))
  
  lvls <- df_sorted %>% 
    pull({{sort_var}}) %>%
    unique()
  
  df <- df %>% mutate({{sort_var}} := 
                       factor({{sort_var}}, levels= lvls))
  
  df
}
sort_descending(group_income, rincome, "$25000 or more", marital)

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