I have a simple function that works just fine on one data frame but doesn’t do anything when I use it in lapply.

For example:

df1 <- data.frame(x = c(1:5), y = c(11:14, NA))  
df2 <- data.frame(x = c(1:3, NA, 4), y = c(11:15))  
mylist <- list(df1 = df1, df2 = df2)  

ref <- data.frame(table = c("df1", "df2"), column = c("y", "x"))

updateCols <- function(table) {
  
  tableName = deparse(substitute(table))
  
  table %>%
    mutate(across(all_of(filter(
      ref, table == tableName) %>% pull(column)),
      ~ as.character(.) %>%
        replace_na("\N")))
}

My updateCols() function applies a mutate on any columns in the reference list ref, converting NA values to N.

When I apply the function one data frame at a time, it works great.

df3 <- updateCols(df1)
df4 <- updateCols(df2)
newlist <- list(df3 = df3, df4 = df4)
print(newlist)

$df3
  x   y
1 1  11
2 2  12
3 3  13
4 4  14
5 5 \N

$df4
    x  y
1   1 11
2   2 12
3   3 13
4 \N 14
5   4 15

However, if I use lapply with it, I don’t get any errors but the function doesn’t do anything.

newlist <- lapply(mylist, updateCols)
print(newlist)

$df1
  x  y
1 1 11
2 2 12
3 3 13
4 4 14
5 5 NA

$df2
   x  y
1  1 11
2  2 12
3  3 13
4 NA 14
5  4 15

Is this a problem with the filtering? Something off with mutate? I’m at a loss.