跨嵌套列表的 rbind 数据帧

Question

我看过各种 rbinding 列表问题，例如 this，但我真的找不到更有效的方法。

我有一个嵌套列表 nestlist，其中包含三个列表，每个列表包含两个数据框：

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)

我想找到一种更简单的方法，通过公共 value 列对列表 1、列表 2 和列表 3 中的每个对象进行 rbind，这样我最终得到：

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

Answer 1

您可以使用 do.call(Map, ...)，这会将嵌套列表作为参数传递给 Map，Map 将以并行方式循环遍历这些列表并调用 rbind，因为 Map 函数将绑定同一位置一起列出：

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

Answer 2

我们可以试试

library(purrr)
lapply(transpose(nestedlist), function(x) do.call(rbind, x))

或使用 dplyr

中的 bind_rows

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

跨嵌套列表的 rbind 数据帧

rbind dataframes across nested lists

nested

r

list

rbind