问题
I've had a look at various rbinding list questions such as this but I can't really find a more efficient way of doing this.
I have a nested list nestlist that contains three lists which each contain two dataframes:
df1 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueA = seq(0.1,0.4,0.1), Category= "Apples")
df2 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueB = seq(0.1,0.4,0.1), Category= "Apples")
list1 <- list(df1,df2)
df3 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueA = seq(0.1,0.4,0.1), Category= "Pears")
df4 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueB = seq(0.1,0.4,0.1), Category= "Pears")
list2 <- list(df3,df4)
df5 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueA = seq(0.1,0.4,0.1), Category= "Stairs")
df6 <- data.frame(ID = paste0(LETTERS[1:4],1:4), valueB = seq(0.1,0.4,0.1), Category= "Stairs")
list3 <- list(df5,df6)
nestedlist <- list(list1,list2,list3)
I want to find an easier way to rbind each object from list1, list2 and list 3 by the common value column so that I end up with:
rbind(nestedlist[[1]][[1]],nestedlist[[2]][[1]], nestedlist[[3]][[1]])
ID A Category
1 A1 0.1 Apples
2 B2 0.2 Apples
3 C3 0.3 Apples
4 D4 0.4 Apples
5 A1 0.1 Pears
6 B2 0.2 Pears
7 C3 0.3 Pears
8 D4 0.4 Pears
9 A1 0.1 Stairs
10 B2 0.2 Stairs
11 C3 0.3 Stairs
12 D4 0.4 Stairs
回答1:
You can use do.call(Map, ...), this passes the nested lists as arguments to Map which will loop through these lists in a parallel way and call rbind as the Map function will bind lists at the same positions together:
do.call(Map, c(f = rbind, nestedlist))
# [[1]]
# ID valueA Category
# 1 A1 0.1 Apples
# 2 B2 0.2 Apples
# 3 C3 0.3 Apples
# 4 D4 0.4 Apples
# 5 A1 0.1 Pears
# 6 B2 0.2 Pears
# 7 C3 0.3 Pears
# 8 D4 0.4 Pears
# 9 A1 0.1 Stairs
# 10 B2 0.2 Stairs
# 11 C3 0.3 Stairs
# 12 D4 0.4 Stairs
#
# [[2]]
# ID valueB Category
# 1 A1 0.1 Apples
# 2 B2 0.2 Apples
# 3 C3 0.3 Apples
# 4 D4 0.4 Apples
# 5 A1 0.1 Pears
# 6 B2 0.2 Pears
# 7 C3 0.3 Pears
# 8 D4 0.4 Pears
# 9 A1 0.1 Stairs
# 10 B2 0.2 Stairs
# 11 C3 0.3 Stairs
# 12 D4 0.4 Stairs
回答2:
We can try
library(purrr)
lapply(transpose(nestedlist), function(x) do.call(rbind, x))
Or use bind_rows from dplyr
library(dplyr)
transpose(nestedlist) %>%
map(bind_rows)
#[[1]]
# ID valueA Category
#1 A1 0.1 Apples
#2 B2 0.2 Apples
#3 C3 0.3 Apples
#4 D4 0.4 Apples
#5 A1 0.1 Pears
#6 B2 0.2 Pears
#7 C3 0.3 Pears
#8 D4 0.4 Pears
#9 A1 0.1 Stairs
#10 B2 0.2 Stairs
#11 C3 0.3 Stairs
#12 D4 0.4 Stairs
#[[2]]
# ID valueB Category
#1 A1 0.1 Apples
#2 B2 0.2 Apples
#3 C3 0.3 Apples
#4 D4 0.4 Apples
#5 A1 0.1 Pears
#6 B2 0.2 Pears
#7 C3 0.3 Pears
#8 D4 0.4 Pears
#9 A1 0.1 Stairs
#10 B2 0.2 Stairs
#11 C3 0.3 Stairs
#12 D4 0.4 Stairs
来源：https://stackoverflow.com/questions/41596326/rbind-dataframes-across-nested-lists