I have a list of lists. The big list is composed by list A, B, C and each of these letters is composed of a list with two dataframes. See below:
ListAll = list(list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("red", "blue"), 5))),
list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("blue", "red"), 5))),
list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("red", "blue"), 5))))
names(ListAll) = c("A", "B", "C")
> ListAll
$A
$A$data
a b c
1 -2.53712026 -0.6694815 2.0284354
2 0.82611084 1.4536211 2.1929939
3 0.17368971 0.2681694 -0.7438975
4 -0.08234772 -0.9999586 -0.2801080
5 -4.02607175 -0.7535428 -0.3388808
6 -1.63180889 -0.1910306 1.0356928
7 -1.33313693 -0.9250792 0.5803261
8 0.88087036 -0.3548668 -0.3731106
9 -0.77262301 0.7583444 -1.9437539
10 0.06084087 -1.0525777 -0.2681174
$A$char
L3 Color
1 l red
2 g blue
3 m red
4 h blue
5 q red
6 d blue
7 a red
8 s blue
9 o red
10 t blue
$B
$B$data
a b c
1 -0.36633900 -0.47905641 -0.78860596
2 -0.37072977 1.96669745 -0.36168884
3 0.07639764 -1.82932608 0.65566462
4 0.29858227 0.09976703 -0.11711302
5 0.77847744 0.27128421 0.75654492
6 0.89522882 1.28713178 -0.96608108
7 0.11443759 -0.99962094 -0.11501575
8 -0.11920869 0.43800235 -1.09136876
9 -0.58772063 -1.94333868 -1.72354096
10 -2.33637437 -0.52737344 0.02056622
$B$char
L3 Color
1 k blue
2 d red
3 s blue
4 z red
5 x blue
6 u red
7 p blue
8 t red
9 l blue
10 v red
$C
$C$data
a b c
1 -0.6366169 0.06446953 -0.02150794
2 -3.3466860 -0.87783521 0.46069701
3 -0.1865610 -0.69112686 0.09725638
4 -0.3280284 -0.59064344 0.35889595
5 0.3922027 -0.04336874 0.97091651
6 -0.7290331 -1.60534590 0.11241533
7 1.3195515 0.18069203 -0.32894485
8 0.6107493 -0.03220736 -2.40375652
9 0.9425496 2.32873530 0.77154078
10 -0.4656241 -0.35425911 0.53269487
$C$char
L3 Color
1 o red
2 x blue
3 g red
4 k blue
5 a red
6 p blue
7 h red
8 w blue
9 n red
10 s blue
11 o red
12 x blue
13 g red
14 k blue
15 a red
16 p blue
17 h red
18 w blue
19 n red
20 s blue
From this list, I would like to have the dataframe data and only the column 2 (Color) of the dataframe char of A, B and C, then have them in a dataframe, like this:
.id a b c Color
1 A -0.269213166 1.25959696 0.60815096 red
2 A -0.673893796 1.20581201 1.34714525 blue
3 A 0.241470346 -1.52928110 0.26428783 red
4 A 1.208567627 -1.07829166 1.80748543 blue
5 A -0.007692734 -0.86438548 -1.64096665 red
6 A -2.017163360 -0.48675333 -1.67662652 blue
7 A -0.633148300 -2.18180234 -0.04390119 red
8 A 1.463925875 -0.73571593 0.42213125 blue
9 A 0.003649150 -1.65524103 -0.98250787 red
10 A 1.138650189 0.84001979 -0.94617824 blue
11 B -0.251018082 1.01930668 0.54220304 blue
12 B -0.095962972 0.62334767 0.11791738 red
13 B -0.696342795 -1.56159037 -0.26576622 blue
14 B 0.870936972 -0.01171982 -0.39033396 red
15 B 0.187987981 -0.17495084 -1.35257925 blue
16 B -0.346946647 -0.43859714 -1.11467490 red
17 B -1.042017149 -0.78778432 0.81739490 blue
18 B -2.174102096 -0.47316699 -2.30049184 red
19 B 0.722957032 -0.74404910 1.46612141 blue
20 B 0.491792528 0.49700033 -0.72193117 red
21 C -0.016289926 0.07519843 0.71536429 red
22 C -0.234032445 -1.36138903 0.15231631 blue
23 C 1.192632593 -0.96278902 1.60867489 red
24 C -0.037066726 1.32362311 0.32692901 blue
25 C -0.600207546 -1.27953645 1.07315190 red
26 C -1.153873839 -1.15354816 -0.99859212 blue
27 C 0.217616268 0.48432038 0.05511501 red
28 C 0.817652920 -0.69406053 -0.24095757 blue
29 C 0.645816458 1.44073689 0.92930204 red
30 C 1.880040619 0.62055981 0.43319005 blue
I tried:
L = lapply(ListAll, function(x) x$data|x$char[2])
or
L = lapply(ListAll, function(x) x[[1]]|x[[2]][2])
and to the dataframe, I would run:
ldply(L, .fun=identity)
but the lapply only works to one element per time
lapply(ListAll function(x) x$data
or
lapply(ListAll, function(x) x$char[2]
How can I subset my list to have specific what I need?
CodePudding user response：
Here is a base R way.
First loop with lapply through the list and extract and cbindthe wanted data and columns. Then, a second lapply loop creates the .id column. The lists are rbind'ed together with do.call.
set.seed(2022)
ListAll = list(list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("red", "blue"), 5))),
list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("blue", "red"), 5))),
list(data = data.frame( a = rnorm(10), b = rnorm(10), c = rnorm(10)),
char = data.frame(L3 = sample(letters, 10), Color = rep (c("red", "blue"), 5))))
names(ListAll) = c("A", "B", "C")
L <- lapply(ListAll, \(x) cbind(x$data, Color = x$char[2]))
L <- do.call(rbind, lapply(seq_along(L), \(i) {
L[[i]]$`.id` <- names(L)[i]
L[[i]][c(5, 1:4)]
}))
L
#> .id a b c Color
#> 1 A 0.90014199 1.00618570 0.36446078 red
#> 2 A -1.17334577 -0.18514603 0.38365100 blue
#> 3 A -0.89748536 -0.98182671 1.11340572 red
#> 4 A -1.44450140 0.09290795 1.21150979 blue
#> 5 A -0.33101358 -0.05278440 -0.34832546 red
#> 6 A -2.90062899 -0.08032790 -0.85955345 blue
#> 7 A -1.05925573 -0.65410367 0.65002719 red
#> 8 A 0.27795474 -0.95068351 0.32805913 blue
#> 9 A 0.74948592 1.01956176 -0.51794657 red
#> 10 A 0.24158254 0.85904641 -0.23898215 blue
#> 11 B -0.16872026 0.36817344 0.41592754 blue
#> 12 B -0.26903769 1.69319002 -1.33844239 red
#> 13 B 0.80776842 0.99583702 -1.29197474 blue
#> 14 B -1.12471724 0.18675214 -0.30907421 red
#> 15 B -1.43078802 1.23833740 0.15651209 blue
#> 16 B 0.06035668 0.30937330 -0.83391675 red
#> 17 B -0.79298250 0.63571793 -0.02454928 blue
#> 18 B 0.34027593 0.02318327 -1.13735155 red
#> 19 B -0.25946873 1.17786360 1.07205425 blue
#> 20 B -1.30484865 -0.45354660 2.31449858 red
#> 21 C 1.29847651 -0.38394914 0.51793514 red
#> 22 C 1.35567805 -0.97585695 0.71217646 blue
#> 23 C 1.35203582 -0.78390718 1.58281914 red
#> 24 C -1.62961506 -1.09959065 -0.41238653 blue
#> 25 C 0.61440940 -1.37465043 0.85369834 red
#> 26 C 0.99671740 -0.45036800 -1.17205398 blue
#> 27 C -0.88329764 -0.02765994 -0.30639866 red
#> 28 C 0.42093350 0.06869818 0.53687936 blue
#> 29 C 2.16138816 0.30745958 -0.29881872 red
#> 30 C -1.22360972 0.24673189 -0.75251562 blue
Created on 2022-05-04 by the reprex package (v2.0.1)
CodePudding user response：
If I interpret the OP correctly I assume that he wants two seperate appended data.frames, one for the data and one for the colors in char.
method 1
Apply two times over your nested list and rbind the results.
data <- do.call(rbind, lapply(ListAll, function(x) x$data))
char <- do.call(rbind, lapply(ListAll, function(x) x$char[2]))
method 2
You can also unlist but note the recursive = FALSE! We then just need the odd ones to get data, and the even ones to get char. Note this might be faster, but can become risky if you do not always have this strict pairs.
t <- unlist(ListAll, recursive = FALSE)
data <- do.call(rbind, t[c(1:length(t))[c(T,F)]])
char <- do.call(rbind, t[c(1:length(t))[c(F,T)]])
char[, 1] <- NULL