R, applying function on multiple elements - r

Question

My function is defined as the following, where i subset a dataframe to a specific name and return the first 5 elements.
Bestideas <- function(x) {
topideas <- subset(Masterall, Masterall$NAME == x) %>%
slice(1:5)
return(topideas)
I would then like to apply the function, to an entire df (with one column of Names), so that the function is applied to each name on the list and binds it into a new df, containing the first five ideas from all unique names. Through research - I have arrived at the following:
bestideas_collection = lapply(UNIQUE_NAMES_DF, Bestideas) %>% bind_rows()
However, it doesn't work. It returns a dataframe with only five ideas in total, and from 5 different names. As there is 30 Unique names in my list, I expected 30*5 = 150 ideas in the "bestideas_collection" variable. I get this error message:
"longer object length is not a multiple of shorter object lengthlonger object length is not a multiple of shorter object length"
Further, if I do it manually for each name, it works just as intended - which makes me think that the function works fine, and that the issue is with the lapply function.
holder <- Bestideas("NAME 1")
bestideas_collection <- bind_rows(bestideas_collection,holder)
holder <- Bestideas("NAME 2")
bestideas_collection <- bind_rows(bestideas_collection,holder)
holder <- Bestideas("NAME 3")
bestideas_collection <- bind_rows(bestideas_collection,holder)
...
Can anyone help me if I am using the function wrong, or do you have alternative methods of doing it? I have already tried with a for-loop - but it gives me the same error as with the lapply function.

Answer 1

I don't have your data, so I tried to reproduce your problem on a fabricated set. I was unable to do so. With a very simple case, your function works as expected.
library(dplyr)
set.seed(123)
Masterall <- data.frame(NAME = rep(LETTERS, 10), value = rnorm(260)) %>%
group_by(NAME) %>% arrange(desc(value))
UNIQUE_NAMES_DF <- LETTERS
lapply(UNIQUE_NAMES_DF, Bestideas) %>% bind_rows()
# A tibble: 130 x 2
# Groups: NAME [26]
NAME value
<chr> <dbl>
1 A 1.65
2 A 1.44
3 A 0.838
4 A 0.563
5 A 0.181
6 B 1.37
7 B 0.452
8 B 0.153
9 B -0.0450
10 B -0.0540
# ... with 120 more rows
Is your UNIQUE_NAMES_DF a data.frame? If so, that is the trouble. The lapply function expects a vector as its first input. It can handle a data.frame, but clearly unexpected results occur. Here is an example:
UNIQUE_NAMES_DF <- data.frame(NAME = LETTERS, other = sample(letters))
lapply(UNIQUE_NAMES_DF, Bestideas) %>% bind_rows()
# A tibble: 12 x 2
# Groups: NAME [11]
NAME value
<chr> <dbl>
1 C -0.785
2 D 0.385
3 E -0.371
4 F 1.13
5 I 1.10
6 N -0.641
7 P -1.02
8 Q -0.0341
9 U -1.07
10 X -0.0834
11 Z 1.26
12 Z -0.739
I do not know the structure of your UNIQUE_NAMES_DF, but if you just feed the column with the names into your lapply, it should work:
lapply(UNIQUE_NAMES_DF$NAME, Bestideas) %>% bind_rows()
# A tibble: 130 x 2
# Groups: NAME [26]
NAME value
<chr> <dbl>
1 A 1.65
2 A 1.44
3 A 0.838
4 A 0.563
5 A 0.181
6 B 1.37
7 B 0.452
8 B 0.153
9 B -0.0450
10 B -0.0540
# ... with 120 more rows