mjhjmtu

Is there a better and nicer way to convert named list with mixed content to data frame?

The working example:

my_list <- list("a" = 1.0, "b" = "foo", "c" = TRUE)

my_df <- data.frame(
 "key" = names(my_list),
 stringsAsFactors = F
)

my_df[["value"]] <- unname(my_list)

Is it possible to do this conversion in one step?

We can use stack from base R

stack(my_list)

According to ?stack

The stack function is used to transform data available as separate columns in a data frame or list into a single column that can be used in an analysis of variance model or other linear model. The unstack function reverses this operation.

Or with enframe

library(tidyverse)
enframe(my_list) %>% # creates the 'value' as a `list` column
 mutate(value = map(value, as.character)) %>% # change to single type
 unnest 

You can use dplyr::as_tibble to coerce the list into a data frame / tibble. This will automatically create a data frame where the list's names are column names, and the list items correspond to rows.

library(dplyr)
library(tidyr)

my_list <- list("a" = 1.0, "b" = "foo", "c" = TRUE)

as_tibble(my_list)
#> # A tibble: 1 x 3
#> a b c 
#> <dbl> <chr> <lgl>
#> 1 1 foo TRUE

To reshape into the two-column format you have, pipe it into tidyr::gather, where the default column names are key and value. Because of the different data types in the column value, this will coerce all the values to character.

as_tibble(my_list) %>%
 gather()
#> # A tibble: 3 x 2
#> key value
#> <chr> <chr>
#> 1 a 1 
#> 2 b foo 
#> 3 c TRUE

^{Created on 2018-11-09 by the reprex package (v0.2.1)}