creating summary of subset filtered dataframe

[str_guru]

I am trying filtered data with value having 1 but the dataframe is already labelled . so the objective is to create a summary of filtered dataset

df <- data.frame(NY = c(1,2,1,1,2,1,1,1,2,1,1,1,2,1),
                 DE = c(2,2,1,1,1,2,2,1,1,1,2,2,2,1) )


df$NY<- factor(df$NY, levels =c(1,2), labels = c("available","unavailable"))
df$DE<- factor(df$DE, levels =c(1,2), labels = c("recieved","rejected"))


tbl <- function(df,col1,col2){

  tb <- df %>% filter(col1== "available" & col2 == "recieved") 
  tb <- table(df[[col1]],df[[col2]]) %>% as.data.frame()
  tb
  
}

output is the frequency of "available" in both column available/ total frequency in NY and DE for "recieved"

the output should be look like

[nirgrahamuk]

your example data and your statement of your goal and your example img do not appear to agree ...
but maybe if you see a solution you will work to clarify your requirements.

tbl <- function(df, col1, col2) {
  df %>%
    summarise(
      c1_avail = sum({{ col1 }} == "available"),
      c2_avail = sum({{ col2 }} == "available"),
      c1_recie = sum({{ col1 }} == "recieved"),
      c2_recie = sum({{ col2 }} == "recieved")
    ) %>%
    mutate(ratio = (c1_avail + c2_avail) / (c1_recie + c2_recie))
}

tbl(df, NY, DE)