Can you provide a reprex with sample data ? It would be easier to answer.
I understood that you have a list column with some element of the list that have some NULL element you want to replace by NA. It is the example I took to show how to use purrr function map to manipulate list column with dplyr.
It just another solution showing the use of purrr
library(dplyr, warn.conflicts = F)
library(purrr)
tab <- data_frame(Group =c(1, 2), list_col =list(list(NULL, 3, 2), list(5, 4, NULL)))
tab %>% glimpse()
#> Observations: 2
#> Variables: 2
#> $ Group <dbl> 1, 2
#> $ list_col <list> [[NULL, 3, 2], [5, 4, NULL]]
tab %>%
mutate(list_col_without_na = map(tab$list_col, ~ map_dbl(.x, ~ if_else(is_null(.x), NA_real_, .x)))) %>%
glimpse()
#> Observations: 2
#> Variables: 3
#> $ Group <dbl> 1, 2
#> $ list_col <list> [[NULL, 3, 2], [5, 4, NULL]]
#> $ list_col_without_na <list> [<NA, 3, 2>, <5, 4, NA>]
Depending on your data and use case, you have to adapt it but the principle is here. map allows you to iterate through each element of a list column to apply some function. (here another map to iterate, find NULL value and replace by NA.
If you want to do other thing on a list column that replace something, it is a mechanism good to know.