using `table()` in list-column of nested data

nested_data_table.R

library(dplyr)

mtcars %>% 
  nest_by(gear) %>% 
  mutate(freq = rlang::list2(
    "gear_{gear}_carb" := table(data$carb)
  )) %>% 
  pull(freq)

#> $gear_3_carb
#> 
#> 1 2 3 4 
#> 3 4 3 5 
#> 
#> $gear_4_carb
#> 
#> 1 2 4 
#> 4 4 4 
#> 
#> $gear_5_carb
#> 
#> 2 4 6 8 
#> 2 1 1 1 

mtcars %>% 
  nest_by(gear) %>% 
  mutate(freq = rlang::list2(
    "gear_{gear}" := count(data, carb)
  )) %>% 
  pull(freq)

#> $gear_3
#> # A tibble: 4 × 2
#> carb     n
#> <dbl> <int>
#> 1     1     3
#> 2     2     4
#> 3     3     3
#> 4     4     5
#> 
#> $gear_4
#> # A tibble: 3 × 2
#> carb     n
#> <dbl> <int>
#> 1     1     4
#> 2     2     4
#> 3     4     4
#> 
#> $gear_5
#> # A tibble: 4 × 2
#> carb     n
#> <dbl> <int>
#> 1     2     2
#> 2     4     1
#> 3     6     1
#> 4     8     1

This works too:

tablefun_quoted <- function(data, xvar){
  data %>% 
    count(.data[[xvar]])   
} 


mtcars %>% 
  nest_by(gear) %>% 
  mutate(freq = list(
    tablefun_quoted(data, "carb")
    )
  ) %>% 
  pull(freq)

# [[1]]
# # A tibble: 4 × 2
# carb     n
# <dbl> <int>
# 1     1     3
# 2     2     4
# 3     3     3
# 4     4     5
# 
# [[2]]
# # A tibble: 3 × 2
# carb     n
# <dbl> <int>
# 1     1     4
# 2     2     4
# 3     4     4
# 
# [[3]]
# # A tibble: 4 × 2
# carb     n
# <dbl> <int>
# 1     2     2
# 2     4     1
# 3     6     1
# 4     8     1

We can also rewrite the function to use unquoted object names:

tablefun_unquoted <- function(data, xvar){
    count(data, {{ xvar }})   
} 


mtcars %>% 
  nest_by(gear) %>% 
  mutate(freq = list(
    tablefun_unquoted(data, carb)
    )
  ) %>% 
  pull(freq)
#> same output as above