---

There are many cases in which you might want to convert a list to a data frame in R. This tutorial explains three different ways to do so.

Method 1: Base R

The following code snippet shows how to convert a list to a data frame using only base R:

#create list
my_list <- list(letters[1:5], letters[6:10])
my_list

[[1]]
[1] "a" "b" "c" "d" "e"

[[2]]
[1] "f" "g" "h" "i" "j"

#convert list to data frame
data.frame(t(sapply(my_list,c)))

  X1 X2 X3 X4 X5
1  a  b  c  d  e
2  f  g  h  i  j

In this example, sapply converts the list to a matrix, then data.frame converts the matrix to a data frame. The end result is a data frame of two rows and five columns.

Method 2: Data Table

The following code snippet shows how to convert a list of two nested lists into a data frame with two rows and three columns using the function from the data.table library:

#load data.table library
library(data.table)

#create list
my_list <- list(a = list(var1 = 1, var2 = 2, var3 = 3),
                b = list(var1 = 4, var2 = 5, var3 = 6))
my_list 

$a
$a$var1
[1] 1

$a$var2
[1] 2

$a$var3
[1] 3

$b
$b$var1
[1] 4

$b$var2
[1] 5

$b$var3
[1] 6

#convert list to data frame
rbindlist(my_list)

   var1 var2 var3
1:    1    2    3
2:    4    5    6

This results in a data table with two rows and three columns. If you’d like to convert this data table to a data frame, you can simply use as.data.frame(DT).

This method converts a list to a data frame faster than the previous method if you’re working with a very large dataset.

Method 3: Dplyr

The following code snippet shows how to convert a list of two nested lists into a data frame with two rows and three columns using the function from the dplyr library:

#load library
library(dplyr)

#create list
my_list <- list(a = list(var1 = 1, var2 = 2, var3 = 3),
                b = list(var1 = 4, var2 = 5, var3 = 6))

my_list

$a
$a$var1
[1] 1

$a$var2
[1] 2

$a$var3
[1] 3


$b
$b$var1
[1] 4

$b$var2
[1] 5

$b$var3
[1] 6

#convert list to data frame
bind_rows(my_list)

# A tibble: 2 x 3
   var1  var2  var3
    
1     1     2     3
2     4     5     6

This results in a data frame with two rows and three columns.

This method also tends to work faster than base R when you’re working with large datasets.