How to merge dataframe lists of unequal length? - r

Question

This question is similar to Joining dataframes from lists of unequal length.
I have a shiny script where I am using fileImport to allow the user to import a variable number of data files. Each datafile is then split into a list of dataframes, and these are imported as a list. So I have a list of a list of dataframes.
The input datafiles have two format possibilities, one may be 129 dataframes long, the other may be 67 - where the 67 is actually a subset of the 129 (so all 67 are present in the 129, but not all 129 are present in the 67). I am then trying to rbind the dataframes by name.
A reproducible example:
# Some data
df.l1 <- list(df1 = data.frame(A = letters[1:10],
B = rnorm(10, 5, 1)),
df2 = data.frame(A = letters[11:20],
B = rnorm(10, 10, 2)))
df.l2 <- list(df1 = data.frame(A = letters[1:10],
B = rnorm(10, 5, 1)),
df2 = data.frame(A = letters[11:20],
B = rnorm(10, 10, 2)))
df.l3 <- list(df1 = data.frame(A = letters[1:10],
B = rnorm(10, 5, 1)),
df2 = data.frame(A = letters[11:20],
B = rnorm(10, 10, 2)),
df3 = data.frame(A = LETTERS[1:10],
B = rnorm(10, 15, 2)))
This works when binding lists of equal length (e.g. df.l1 and df.l2)
df.two <- list(df.l1, df.l2)
list.merged <- do.call(function(...) Map(rbind, ...), df.two)
But fails when binding list of dataframes with variables lengths.
df.three <- list(df.l1, df.l2, df.l3)
list.merged <- do.call(function(...) Map(rbind, ...), df.three)
Giving the error:
Warning messages:
1: In mapply(FUN = f, ..., SIMPLIFY = FALSE) :
longer argument not a multiple of length of shorter
2: In mapply(FUN = f, ..., SIMPLIFY = FALSE) :
longer argument not a multiple of length of shorter
As I said above, similar questions have been asked, but this situation is unique given the variable number of lists I am trying to merge. Help is greatly appreciated!

Answer 1

For a robust handling of this I would use dplyr::bind_rows or data.table::rbindlist. First you bind each list, then you bind at the upper level:
tidyverse version:
library(dplyr)
bind_rows(lapply(df.three, bind_rows))
data.table version:
library(data.table)
rbindlist(lapply(df.three, rbindlist))
Not only will this handle weird corner cases you don't expect, but it will also be much faster than do.call.
edit in response to comment
Try this:
library(purrr)
library(dplyr)
df_names <- unique(unlist(sapply(df.three, names)))
result <- list()
for (n in df_names) {
result[[n]] <- map(df.three, n)
}
map(result, dplyr::bind_rows)