使用字符向量对命名数据帧的嵌套列表进行索引-R [英] Index nested lists of named data frames using character vector - R

问题描述

我有一个嵌套的命名数据框列表，如下所示:

I have a nested list of named data frames like so:

mylist2 <- list(
  list(df1.a = data.frame(replicate(2,sample(0:1,5,rep=TRUE))), df2.b = data.frame(replicate(2,sample(0:1,5,rep=TRUE)))),
  list(df3.c = data.frame(replicate(2,sample(0:1,5,rep=TRUE))), df4.d = data.frame(replicate(2,sample(0:1,5,rep=TRUE)))),
  list(df5.e = data.frame(replicate(2,sample(0:1,5,rep=TRUE))), df6.f = data.frame(replicate(2,sample(0:1,5,rep=TRUE)))))

我运行了一个测试(哪种测试并不重要)，它会生成一个字符向量，告诉我此列表中的哪些数据帧很重要:

I run a test (not important what sort of test) and it produces a character vector telling me which data frames in this list are important:

test
[1] "df1.a" "df5.e"

使用此字符向量从嵌套列表中提取这些数据帧的最有效方法是什么?该测试仅显示第二个列表的名称，因此nestedlist[test]不起作用.

What is the most efficient way to extract these data frames from the nested list using this character vector? The test only shows the names of second list, so nestedlist[test] does not work.

推荐答案

由于OP提到它是嵌套的list，因此我们可以遍历初始的list，然后使用以下命令提取第二个list的元素[

As the OP mentioned it was a nested list, we can loop through the initial list and then extract the elements of the second list with [

lapply(mylist2, '[', test)

---

或使用tidyverse

library(tidyverse)
map(mylist2, ~ .x %>% 
                   select(test))

更新

基于更新后的数据集:

Update

Based on the updated dataset:

Filter(length, lapply(mylist2, function(x) x[intersect(test, names(x))]))

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