自动从列表列表的元素创建变量R

Question

我有一个如下列表

str(list_ts_split)
List of 5
 $ date    :List of 2
  ..$ train: Time-Series [1:24] from 2019 to 2021: 1.55e+09 1.55e+09 1.55e+09 1.55e+09 
1.56e+09 ...
  ..$ test : Time-Series [1:6] from 2021 to 2021: 1.61e+09 1.61e+09 1.61e+09 1.62e+09 1.62e+09 
...
 $ actualB1:List of 2
  ..$ train: Time-Series [1:24] from 2019 to 2021: 5463 7618 3745 6760 5856 ...
  ..$ test : Time-Series [1:6] from 2021 to 2021: 5535 7326 6195 2435 3041 ...
     $ actualB2:List of 2
  ..$ train: Time-Series [1:24] from 2019 to 2021: 6523 1734 9544 4687 8076 ...
  ..$ test : Time-Series [1:6] from 2021 to 2021: 3647 9272 4974 5931 1459 ...
 $ actualAx:List of 2
  ..$ train: Time-Series [1:24] from 2019 to 2021: 193 200 310 149 719 357 470 623 678 533 ...
  ..$ test : Time-Series [1:6] from 2021 to 2021: 274 142 968 831 178 184
 $ actualAy:List of 2
  ..$ train: Time-Series [1:24] from 2019 to 2021: 3053 4351 3284 2155 1805 ...
  ..$ test : Time-Series [1:6] from 2021 to 2021: 8236 1585 2324 5692 4249 ...

我可以使用下面的代码访问列表列表的元素

df1_tstrain <- list_ts_split$actualB1$train

df1_tstest <- list_ts_split$actualB1$test

list_ts_split $actualB1$train
      Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
 2019 5463 7618 3745 6760 5856 2645 4061 1162 6829 7584 8383 4016
 2020 2827 1666 3753 2004 1757 9360 5989 9031 1584 1435 8365 9209

 list_ts_split$actualB1$test
       Jan  Feb  Mar  Apr  May  Jun
  2021 5535 7326 6195 2435 3041 2737

EDIT1：我的问题是，无论如何要创建一个循环或使用一个函数来做同样的事情 df1_tstrain

EDIT2：

我现在正在尝试类似下面的东西

for (i in 1:length(list_ts_split)){
assign(paste0("tstrain",i}.as.data.frame(list_ts_split[[i]]))
}

Answer 1

你没有一个有效的例子，所以我不确定我是否理解你的问题。话虽如此，这里有一些东西可以尝试。

## Some data to work with
lst <- list(
  date = list(
    train = 2000:2010,
    test  = 2011:2021
  ),
  actualB1 = list(
    train = 2000:2010,
    test  = 2011:2021
  ),
  actualAx = list(
    train = 2000:2010,
    test  = 2011:2021
  )
)
## A function to subset the list at levels 1 and 2.
f <- function(lst, level_1, level_2){
  # l1 <- lst[[level_1]]
  # l1[[level_2]] 
  l1 <- sapply(X = lst, FUN = "[", level_2, simplify = FALSE)
  l1[[level_1]]
}
## testing the function on the list specifying the names of the 2 levels
test <- f(lst = lst, level_1 = 'actualB1', level_2 = 'train')
test

我仍然不确定我是否理解这个问题，但这是我在递归函数中提出的另一个想法。

## Data

lst <- list(
  date = data.frame(
    train = 2000:2005,
    test  = 2005:2010
  ),
  actualB1 = data.frame(
    train = 2010:2015,
    test  = 2015:2020
  ),
  actualAx = data.frame(
    train = 2020:2025,
    test  = 2030:2035
  )
)

# Function

f <- function(lst){
  names_lst <- names(lst)
  lapply(X = names_lst, function(i){
    if(inherits(lst[[i]], what = 'data.frame', which = TRUE)){
      names_i <- names(lst[[i]])
      lapply(X = names_i, function(j){
        obj_name <- paste(i, j, sep = "_")
        assign(obj_name, lst[[i]][[j]], envir = .GlobalEnv)
      })
    } else {
      f (lst)
    }
  })
}

# Function called on Data

test <- f(lst = lst)

我不确定我是否理解您的问题的原因是，我似乎无法理解为什么要继续对列表进行子集化并将结果分配给新对象。

我认为，如果您想对要进行子集化的数据进行进一步分析，则需要重新考虑您的方法。虽然上面的函数通常会检索列表不同嵌套级别的名称，但它可能会遇到错误C stack usage <number> is too close to the limit，具体取决于您的设置。这可能表明您可能需要重新考虑您的方法。尝试向lst 添加更多级别的嵌套，您最终可能会遇到该错误。在我的机器上，以下导致我出现该错误：

lst <- list(
  date = data.frame(
    train   = 2000:2005,
    test    = 2005:2010
  ),
  actualB1  = data.frame(
    train   = 2010:2015,
    test    = 2015:2020
  ),
  actualAx  = list(
    up      = data.frame(
      train = 2020:2025,
      test  = 2030:2035
    ),
    sub     = data.frame (
      train = 2040:2045,
      test  = 2045:2050
    )
  )
)
test <- f(lst = lst) # Error: C stack usage  15926032 is too close to the limit