Converting a list to a column structure, with the names in column one and the content in column two

Question

I have two types of data.

type_1 <- list(
     "One" = "Something",
     "Two" = "Something Else"
)

type_2 <- list(
     "One" = c(1,2,3),
     "Two" = c(4,5,6)
)

For both types I would like to create dataframes where the left hand side, or listnames (One & Two) are column_one, and where the right hand side are column_two.

I tried a few of these approaches without much success.

What is the correct way to do this?

Desired output:

type_1 <- structure(
    list(column__one = list("One","Two"), column_two = list("Something", "Something Else")), 
    row.names = c("A", "B"), class = "data.frame")

  column__one     column_two
A         One      Something
B         Two Something Else

 type_2 <- structure(
    list(column__one = list("One","Two"), column_two = list(a= c(1,2,3), b=c(4,5,6))), 
    row.names = c("A", "B"), class = "data.frame")

  column__one column_two
A         One    1, 2, 3
B         Two    4, 5, 6

Answer 1

We can use enframe from tibble

library(tibble)
library(tidyr)
enframe(type_1, name = "column_one", value = "column_two") %>% 
    unnest(column_two)
# A tibble: 2 × 2
  column_one column_two    
  <chr>      <chr>         
1 One        Something     
2 Two        Something Else


enframe(type_2, name = "column_one", value = "column_two")
# A tibble: 2 × 2
  column_one column_two
  <chr>      <list>    
1 One        <dbl [3]> 
2 Two        <dbl [3]> 

---

Or in base R with stack

 stack(type_1)[2:1]
  ind         values
1 One      Something
2 Two Something Else

The second one will return a normal column as well

stack(type_2)[2:1]
  ind values
1 One      1
2 One      2
3 One      3
4 Two      4
5 Two      5
6 Two      6

Answer 2

A method with map_dfr() from purrr:

library(tidyverse)

map_dfr(type_1, ~ tibble(column_two = .x), .id = "column_one")

# # A tibble: 2 × 2
#   column_one column_two    
#   <chr>      <chr>         
# 1 One        Something     
# 2 Two        Something Else

map_dfr(type_2, ~ tibble(column_two = list(.x)), .id = "column_one")

# # A tibble: 2 × 2
#   column_one column_two
#   <chr>      <list>    
# 1 One        <dbl [3]> 
# 2 Two        <dbl [3]>