Combine list elements into a dataframe r - r

Question

I currently have a list with columns as individual elements.
I would like to combine list elements with the same column names (i.e. bind rows) and merge across the different columns (i.e. bind columns) into a single data frame. I'm having difficulty finding examples of how to do this.
l = list(est = c(0, 0.062220390087795, 1.1020213968139, 0.0359939361491544
), se = c(0.0737200634874046, 0.237735179934829, 0.18105632705918,
0.111359438298789), rf = structure(c(NA, NA, NA, 4L), levels = c("Never\nsmoker",
"Occasional\nsmoker", "Ex-regular\nsmoker", "Smoker"), class = "factor"),
n = c(187L, 18L, 32L, 82L), model = c("Crude", "Crude", "Crude",
"Crude"), est = c(0, 0.112335510453586, 0.867095253670329,
0.144963556944891), se = c(0.163523775933409, 0.237039485900481,
0.186247776987999, 0.119887623484768), rf = structure(c(NA,
NA, NA, 4L), levels = c("Never\nsmoker", "Occasional\nsmoker",
"Ex-regular\nsmoker", "Smoker"), class = "factor"), n = c(187L,
18L, 32L, 82L), model = c("Model 1", "Model 1", "Model 1",
"Model 1"), est = c(0, 0.107097305324242, 0.8278765140371,
0.0958220447859447), se = c(0.164787596943329, 0.237347836229364,
0.187201880036661, 0.120882616647714), rf = structure(c(NA,
NA, NA, 4L), levels = c("Never\nsmoker", "Occasional\nsmoker",
"Ex-regular\nsmoker", "Smoker"), class = "factor"), n = c(187L,
18L, 32L, 82L), model = c("Model 2", "Model 2", "Model 2",
"Model 2"))
I would like the data to have the following format:
data.frame(
est = c(),
se = c(),
rf = c(),
model = c()
)
Any help would be appreciated. Thank you!

Answer 1

In this solution, first the elements of l are grouped by name and then are combined using c. Finally, the resulting list is converted to a dataframe using map_dfc.
library(dplyr)
library(purrr)
cols <- c("est", "se", "rf", "model")
setNames(cols,cols) |>
map(~l[names(l) == .x]) |>
map_dfc(~do.call(c, .x))
#> # A tibble: 12 × 4
#> est se rf model
#> <dbl> <dbl> <fct> <chr>
#> 1 0 0.0737 NA Crude
#> 2 0.0622 0.238 NA Crude
#> 3 1.10 0.181 NA Crude
#> 4 0.0360 0.111 Smoker Crude
#> 5 0 0.164 NA Model 1
#> 6 0.112 0.237 NA Model 1
#> 7 0.867 0.186 NA Model 1
#> 8 0.145 0.120 Smoker Model 1
#> 9 0 0.165 NA Model 2
#> 10 0.107 0.237 NA Model 2
#> 11 0.828 0.187 NA Model 2
#> 12 0.0958 0.121 Smoker Model 2

Answer 2

another option
library(purrr)
grp <- (seq(length(l)) - 1) %/% 5
l_split <- split(l, grp)
map_df(l_split, c)
#> # A tibble: 12 × 5
#> est se rf n model
#> <dbl> <dbl> <fct> <int> <chr>
#> 1 0 0.0737 <NA> 187 Crude
#> 2 0.0622 0.238 <NA> 18 Crude
#> 3 1.10 0.181 <NA> 32 Crude
#> 4 0.0360 0.111 Smoker 82 Crude
#> 5 0 0.164 <NA> 187 Model 1
#> 6 0.112 0.237 <NA> 18 Model 1
#> 7 0.867 0.186 <NA> 32 Model 1
#> 8 0.145 0.120 Smoker 82 Model 1
#> 9 0 0.165 <NA> 187 Model 2
#> 10 0.107 0.237 <NA> 18 Model 2
#> 11 0.828 0.187 <NA> 32 Model 2
#> 12 0.0958 0.121 Smoker 82 Model 2