How to find the minimum from a column whose elements are list and keep its corresponding other column list valuesg?

I have data frame

df <- data.frame(A = c(1, 2, 3, 4),
conn = c("2, 3, 4", "8, 1, 6", "4, 6, 1, 5", "5, 9, 1, 3"),
ListW = c("100, 100, 100", "60, 100, 100", "100, 50, 100, 100", "100, 10, 100, 100"))

How to find the minimum from ListW and keep its corresponding conn value so that the output would be

df <- data.frame(A = c(1, 2, 3, 4),
Nconn = c("2, 3, 4", "8", "6", "9"),
minListW = c("100", "60", "50", "10"))

Your help would be greatly appreciated and helpful for me, others as well. I have tried with the following

df <- data.frame(A = c(1, 2, 3, 4),
                 conn = c("2, 3, 4", "8, 1, 6", "4, 6, 1, 5", "5, 9, 1, 3"),
                 ListW = c("100, 100, 100", "60, 100, 100", "100, 50, 100, 100", "100, 10, 100, 100"))

df$ListW <- as.character(df$ListW) # Convert ListW column to character type

listW_values <- strsplit(df$ListW, ", ") # Split the ListW values by comma and space
min_values <- sapply(listW_values, function(x) min(as.integer(x))) # Find the minimum value for each ListW value

One option would be to use tidyr::separate_rows to split your columns into rows, then use e.g. dplyr::slice_min to get the minimum(s) per group:

library(tidyr)
library(dplyr, warn = FALSE)

df |>
  separate_rows(conn, ListW, sep = ", ", convert = TRUE) |>
  slice_min(ListW, n = 1, by = A) |>
  summarise(across(c(conn, ListW), ~ paste0(unique(.x), collapse = ", ")), .by = A)
#> # A tibble: 4 × 3
#>       A conn    ListW
#>   <dbl> <chr>   <chr>
#> 1     1 2, 3, 4 100  
#> 2     2 8       60   
#> 3     3 6       50   
#> 4     4 9       10