Stack nested lists of dataframes with purrr

Question

I have a list of lists of dataframes, something like this:

I just edited to change the data so that the length of the list and nested list are not equal.

test <- list(list(cars1 = head(mtcars), iris1 = head(iris)),
             list(cars2 = tail(mtcars), iris2 = tail(iris)),
             list(cars3 = tail(mtcars), iris3 = tail(iris)))

This gives me what I want with a mix of lapply() and purrr.

lapply(1:2, function(x) purrr::map_dfr(test, ~ .[[x]]))

Is there a way to do this more efficiently in a single line just in purrr? This seems like a fairly common task.

Answer 1

Here is an option with purrr

library(dplyr)
library(stringr)
library(purrr)
test %>%
   flatten %>%
   split(str_remove(names(.), '\\d+')) %>%
   map(bind_rows)
#$cars
#    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
#3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#7  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#8  30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
#9  15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#10 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#11 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
#12 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
#13 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#14 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
#15 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#16 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#17 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
#18 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

#$iris
#   Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
#1           5.1         3.5          1.4         0.2    setosa
#2           4.9         3.0          1.4         0.2    setosa
#3           4.7         3.2          1.3         0.2    setosa
#4           4.6         3.1          1.5         0.2    setosa
#5           5.0         3.6          1.4         0.2    setosa
#6           5.4         3.9          1.7         0.4    setosa
#7           6.7         3.3          5.7         2.5 virginica
#8           6.7         3.0          5.2         2.3 virginica
#9           6.3         2.5          5.0         1.9 virginica
#10          6.5         3.0          5.2         2.0 virginica
#11          6.2         3.4          5.4         2.3 virginica
#12          5.9         3.0          5.1         1.8 virginica
#13          6.7         3.3          5.7         2.5 virginica
#14          6.7         3.0          5.2         2.3 virginica
#15          6.3         2.5          5.0         1.9 virginica
#16          6.5         3.0          5.2         2.0 virginica
#17          6.2         3.4          5.4         2.3 virginica
#18          5.9         3.0          5.1         1.8 virginica

---

Or another option is

map_dfr(test, enframe) %>%
     group_split(name = str_remove(name, "\\d+")) %>%
     map( ~ unnest(.x, value))