循环浏览子列表，其中“子子"列表保持不变 [英] Looping through a sub list, where the "sub sub" list stays constant
问题描述
我想遍历一个子列表，其中子子"列表保持不变.我提到的所有代码只是可复制的示例(请注意，实际数据确实很大)，并且应该可以正常工作.
I would like to loop through a sub list, where the "sub sub" list stays constant. All code mentioned by me is just the reproducible example (please note that the actual data is really large) and should work without issue.
我有一个列表列表，每个列表都有2个子列表，如下所示:
I have a list of lists wich each have 2 sub lists as follows:
library(data.table)
library(mice)
df <- fread(
"A B C D E F iso year
0 A NA 1 NA NA NLD 2009
1 Y NA 2 NA NA NLD 2009
0 Q NA 3 NA NA AUS 2011
1 NA NA 4 NA NA AUS 2011
0 0 NA 7 NA NA NLD 2008
1 1 NA 1 NA NA NLD 2008
0 1 NA 3 NA NA AUS 2012
0 NA 1 NA 1 NA ECU 2009
1 NA 0 NA 2 0 ECU 2009
0 NA 0 NA 3 0 BRA 2011
1 NA 0 NA 4 0 BRA 2011
0 NA 1 NA 7 NA ECU 2008
1 NA 0 NA 1 0 ECU 2008
0 NA 0 NA 3 2 BRA 2012
1 NA 0 NA 4 NA BRA 2012",
header = TRUE
)
# Creates a list
df_iso <- split(df, df$iso) # Creates a list of dataframes
# Creates a list of lists
mylist.names <- names(df_iso)
df_iso_list <- vector("list", length(mylist.names))
names(df_iso_list) <- mylist.names
f <- function(x) return(list(a = list(), b = list()))
new_nested <- lapply(df_iso, f)
现在new_nested$AUS$a访问子列表AUS的列表a.到目前为止一切顺利.
Now new_nested$AUS$a accesses the list a of sub list AUS. So far so good.
我想将下面的两个列表(df_iso_1, df_iso_2)重新分配到我刚刚创建的列表结构中.
I would like to redistribute the two lists (df_iso_1, df_iso_2) below to the list structure I just created.
df_iso_1 = list()
for (i in 1:length(df_iso)) {
tryCatch({
df_iso_1 [[i]] <- mice(df_iso[[i]], m=1, maxit = 5, seed=1)
if (i==1000) stop("stop")
}, error=function(e){cat("ERROR :",conditionMessage(e), "\n")})
}
df_iso_2 = list()
for (i in 1:length(df_iso)) {
tryCatch({
df_iso_2 [[i]] <- mice(df_iso[[i]], m=1, maxit = 5, seed=2)
if (i==1000) stop("stop")
}, error=function(e){cat("ERROR :",conditionMessage(e), "\n")})
}
names(df_iso_1) <- names(df_iso)
names(df_iso_2) <- names(df_iso)
尽管new_nested$AUS$a访问列表，但我想遍历带有索引的iso代码，而不是按名称引用它们:
Although new_nested$AUS$a accesses the list, I would like to loop through the iso codes with an index instead of referring to them by name:
for (n in length(df_iso)) {
new_nested$[i]$a <- df_iso_1[n]
}
但是这不起作用.遍历这些列表的正确语法是什么?
This does however not work. What is the correct syntax of looping through these lists?
所需的输出:
在df_iso_1和df_iso_2中，每个iso代码将mids对象池化.换句话说，所有iso代码都被放到新的结构中:
From df_iso_1 and df_iso_2, the mids objects are pooled per iso code. In other words, all iso codes are put together in the new structure:
因此，new_nested的列表NLD充满了df_iso_1和df_iso_2的NLD mids对象，列表列表AUS充满了df_iso_1和df_iso_1的AUS mids对象df_iso_2.
So new_nested has its list NLD filled with the NLD mids objects from df_iso_1 and df_iso_2, and its list list AUS filled with the AUS mids objects from df_iso_1 and df_iso_2.
推荐答案
以下是两种方法.首先是用seq_len(length(df_iso))修复循环并匹配输出，将df_iso_1[n]更改为df_iso1[[n]]:
Here are two approaches. The first is to fix your loop with seq_len(length(df_iso)) and to match your output, changing your df_iso_1[n] to df_iso1[[n]]:
for (n in seq_len(length(df_iso))) {
new_nested[[names(df_iso)[n]]]$a <- df_iso_1[[n]]
new_nested[[names(df_iso)[n]]]$b <- df_iso_2[[n]]
}
new_nested$AUS$a
Class: mids
Number of multiple imputations: 1
Imputation methods:
A B C D E F iso year
"" "" "" "" "" "" "" ""
PredictorMatrix:
A B C D E F iso year
A 0 0 0 0 0 0 0 1
B 0 0 0 0 0 0 0 0
C 0 0 0 0 0 0 0 0
D 1 0 0 0 0 0 0 1
E 0 0 0 0 0 0 0 0
F 0 0 0 0 0 0 0 0
Number of logged events: 6
it im dep meth out
1 0 0 constant B
2 0 0 constant C
3 0 0 constant E
4 0 0 constant F
5 0 0 constant iso
6 0 0 collinear D
第二种方法是使用mapply遍历df_iso_n列表的每个元素，以将它们组合成一个新的列表矩阵:
The second approach is to use mapply to loop through each element of your df_iso_n lists to combine them into a new matrix of lists:
mapply(list, df_iso_1, df_iso_2)
# AUS BRA ECU NLD
#[1,] List,21 List,21 List,21 List,21
#[2,] List,21 List,21 List,21 List,21
mapply(list, df_iso_1, df_iso_2)[, 'AUS']
[[1]]
Class: mids
Number of multiple imputations: 1
Imputation methods:
A B C D E F iso year
"" "" "" "" "" "" "" ""
PredictorMatrix:
A B C D E F iso year
A 0 0 0 0 0 0 0 1
B 0 0 0 0 0 0 0 0
C 0 0 0 0 0 0 0 0
D 1 0 0 0 0 0 0 1
E 0 0 0 0 0 0 0 0
F 0 0 0 0 0 0 0 0
Number of logged events: 6
it im dep meth out
1 0 0 constant B
2 0 0 constant C
3 0 0 constant E
4 0 0 constant F
5 0 0 constant iso
6 0 0 collinear D
[[2]]
Class: mids
Number of multiple imputations: 1
Imputation methods:
A B C D E F iso year
"" "" "" "" "" "" "" ""
PredictorMatrix:
A B C D E F iso year
A 0 0 0 0 0 0 0 1
B 0 0 0 0 0 0 0 0
C 0 0 0 0 0 0 0 0
D 1 0 0 0 0 0 0 1
E 0 0 0 0 0 0 0 0
F 0 0 0 0 0 0 0 0
Number of logged events: 6
it im dep meth out
1 0 0 constant B
2 0 0 constant C
3 0 0 constant E
4 0 0 constant F
5 0 0 constant iso
6 0 0 collinear D
此外，考虑重构代码仍然是一个好主意.这大致上可以完成3行代码:
Also, it still would be a good idea to consider refactoring your code. This largely does everything in 3 lines:
seeds = c(1,2)
by(data = df, INDICES = df$iso,
FUN = function(ISO) lapply(seeds, function(seed) mice(ISO, m = 1, maxit = 5, seed = seed)))
df$iso: AUS
[[1]]
Class: mids
Number of multiple imputations: 1
Imputation methods:
A B C D E F iso year
"" "" "" "" "" "" "" ""
PredictorMatrix:
A B C D E F iso year
A 0 0 0 0 0 0 0 1
B 0 0 0 0 0 0 0 0
C 0 0 0 0 0 0 0 0
D 1 0 0 0 0 0 0 1
E 0 0 0 0 0 0 0 0
F 0 0 0 0 0 0 0 0
Number of logged events: 6
it im dep meth out
1 0 0 constant B
2 0 0 constant C
3 0 0 constant E
4 0 0 constant F
5 0 0 constant iso
6 0 0 collinear D
[[2]]
Class: mids
Number of multiple imputations: 1
Imputation methods:
A B C D E F iso year
"" "" "" "" "" "" "" ""
PredictorMatrix:
A B C D E F iso year
A 0 0 0 0 0 0 0 1
B 0 0 0 0 0 0 0 0
C 0 0 0 0 0 0 0 0
D 1 0 0 0 0 0 0 1
E 0 0 0 0 0 0 0 0
F 0 0 0 0 0 0 0 0
Number of logged events: 6
it im dep meth out
1 0 0 constant B
2 0 0 constant C
3 0 0 constant E
4 0 0 constant F
5 0 0 constant iso
6 0 0 collinear D
----------------------------------------------------
df$iso: BRA
[[1]]
...
这篇关于循环浏览子列表，其中“子子"列表保持不变的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
