R: populate data.frame within function in mapply - r

Question

A data.frame df1 is queried (fuzzy match) against another data.frame df2 with agrep. Via iterating over its output (a list called matches holding the row number of the respective matches in df2), df1 is populated with affiliated values from df2.
The goal is a function that is passed to mapply; however, in all my attempts df1 remains unchanged.
In a for-loop, the code works as expected and populates df1 with the affiliated variables from df2. Still, I would be interested how to solve this with a function that is passed to mapply.
First, the two data.frames:
df1 <- structure(list(Species = c("Alisma plantago-aquatica", "Alnus glutinosa",
"Carex davalliana", "Carex echinata",
"Carex elata"),
CheckPoint = c(NA, NA, NA, NA, NA),
L = c(NA, NA, NA, NA, NA),
R = c(NA, NA, NA, NA, NA),
K = c(NA, NA, NA, NA, NA)),
row.names = c(NA, 5L), class = "data.frame")
df2 <- structure(list(Species = c("Alisma gramineum", "Alisma lanceolatum",
"Alisma plantago-aquatica", "Alnus glutinosa",
"Alnus incana", "Alnus viridis",
"Carex davalliana", "Carex depauperata",
"Carex diandra", "Carex digitata",
"Carex dioica", "Carex distans",
"Carex disticha", "Carex echinata",
"Carex elata"),
L = c(7L, 7L, 7L, 5L, 6L, 7L, 9L, 4L, 8L, 3L, 9L, 9L, 8L,
8L, 8L),
R = c(7L, 7L, 5L, 5L, 4L, 3L, 4L, 7L, 6L, NA, 4L, 6L, 6L,
NA, NA),
K = c(6L, 2L, NA, 3L, 5L, 4L, 4L, 2L, 7L, 4L, NA, 3L, NA,
3L, 2L)),
row.names = seq(1:15), class = "data.frame")
Then, fuzzy match by Species:
matches <- lapply(df1$Species, agrep, x = df2$Species, value = FALSE,
max.distance = c(deletions = 0,
insertions = 1,
substitutions = 1))
Populating df1 with the values from df2 works as expected:
for (i in 1:dim(df1)[1]){
df1[i, 2:5] <- df2[matches[[i]], ]
}
In contrast to my approach with mapply that does return the correct values, although as a list of dissasembled values that are never written into df1. No combination (with or without return(df1), writing it into another variable nor desparate attempts with the state of SIMPLIFY or USE.NAMES) yielded the desired results.
populatedf1 <- function(matches, index){
df1[index, 2:5] <- df2[matches, ]
#return(df1)
}
mapply(populatedf1, matches, seq_along(matches), SIMPLIFY = FALSE,
USE.NAMES = FALSE)
Would be great if someone knows the solution or could point me into a certain direction, thanks! :)

Answer 1

Actually, you would not need any loop here (for or mapply) if you replace lapply with sapply (so that it returns a vector instead of list) and then do a direct assignment.
matches <- sapply(df1$Species, agrep, x = df2$Species, value = FALSE,
max.distance = c(deletions = 0,
insertions = 1,
substitutions = 1))
df1[, 2:5] <- df2[matches,]
df1
# Species CheckPoint L R K
#1 Alisma plantago-aquatica Alisma plantago-aquatica 7 5 NA
#2 Alnus glutinosa Alnus glutinosa 5 5 3
#3 Carex davalliana Carex davalliana 9 4 4
#4 Carex echinata Carex echinata 8 NA 3
#5 Carex elata Carex elata 8 NA 2
As far as your approach is concerned you can use Map or mapply with SIMPLIFY = FALSE and bring the list of dataframes into one dataframe using do.call and rbind and then assign.
df1[, 2:5] <- do.call(rbind, Map(populatedf1, matches, seq_along(matches)))