data_frames (variously called tibbles, tbl_df, tbl) natively support the creation of list columns using the data_frame constructor. To use them, load one of the many libraries with them such as tibble, dplyr or tidyverse.
> data_frame(abc = letters[1:3], lst = list(1:3, 1:3, 1:3))
# A tibble: 3 × 2
abc lst
<chr> <list>
1 a <int [3]>
2 b <int [3]>
3 c <int [3]>
They are actually data.frames under the hood, but somewhat modified. They can almost always be used as normal data.frames. The only exception I've found is that when people do inappropriate class checks, they cause problems:
> #no problem
> data.frame(x = 1:3, y = 1:3) %>% class
[1] "data.frame"
> data.frame(x = 1:3, y = 1:3) %>% class == "data.frame"
[1] TRUE
> #uh oh
> data_frame(x = 1:3, y = 1:3) %>% class
[1] "tbl_df" "tbl" "data.frame"
> data_frame(x = 1:3, y = 1:3) %>% class == "data.frame"
[1] FALSE FALSE TRUE
> #dont use if with improper testing!
> if(data_frame(x = 1:3, y = 1:3) %>% class == "data.frame") "something"
Warning message:
In if (data_frame(x = 1:3, y = 1:3) %>% class == "data.frame") "something" :
the condition has length > 1 and only the first element will be used
> #proper
> data_frame(x = 1:3, y = 1:3) %>% inherits("data.frame")
[1] TRUE
I recommending reading about them in R 4 Data Science (free).