In this example, I have two lists
tiers <- list("tier 1", "tier 2", "tier 3")
main <- list(data.frame(a = c("this", "that")),
data.frame(a = c("the other", "that too")),
data.frame(a = c("once more", "kilgore trout")))
and I'd like to mutate() each list element (i.e., data.frame()) in main by adding the value in tiers from the corresponding element. I thought mapply() would do it:
library(dplyr)
mapply(function(x, y) y %>% mutate(tier = x), tiers, main)
but I get an unexpected result
> mapply(function(x, y) y %>% mutate(tier = x), tiers, main)
[,1] [,2] [,3]
a factor,2 factor,2 factor,2
tier Character,2 Character,2 Character
while what I expected was
[[1]]
a tier
1 this tier 1
2 that tier 1
[[2]]
a tier
1 the other tier 2
2 that too tier 2
[[3]]
a tier
1 once more tier 3
2 kilgore trout tier 3
Am I using mapply() correctly? If not, is there something I should be using to get the result I'm expecting? I should note that actual data may have up to n list elements; I can't hard-code any values in terms of 1:n.
What you needed was to add SIMPLIFY = FALSE in your mapply call
library(dplyr)
mapply(function(x, y) y %>% mutate(tier = x), tiers, main, SIMPLIFY = FALSE)
# a tier
#1 this tier 1
#2 that tier 1
#[[2]]
# a tier
#1 the other tier 2
#2 that too tier 2
#[[3]]
# a tier
#1 once more tier 3
#2 kilgore trout tier 3
?mapply says
SIMPLIFY - attempt to reduce the result to a vector, matrix or higher dimensional array;
SIMPLIFY argument is by default TRUE in mapply and FALSE in Map
Map(function(x, y) y %>% mutate(tier = x), tiers, main)
If you want to keep everything in base R, you could use cbind
Map(cbind, main, tiers)
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