User Defined Function to create and sum a subset in R - r

Question

I need help defining a function that creates a vector in a database where, for each row, the function looks at another column in that database, searches for that value in a designated column of a separate database, creates a subset of that second database consisting of all matching rows, sums a separate column of that new subset, and returns that value to the corresponding row of the new column in the original database.
In other words, I have a data frame that looks something like this:
ID <- c('a', 'b', 'c', 'd', 'e')
M <- 20:39
df <- data.frame(cbind(ID, M))
df$M <- as.numeric(df$M)
> df
ID M
1 a 1
2 b 2
3 c 3
4 d 4
5 e 5
6 a 6
7 b 7
8 c 8
9 d 9
10 e 10
11 a 11
12 b 12
13 c 13
14 d 14
15 e 15
16 a 16
17 b 17
18 c 18
19 d 19
20 e 20
> str(df)
'data.frame': 20 obs. of 2 variables:
$ ID: Factor w/ 5 levels "a","b","c","d",..: 1 2 3 4 5 1 2 3 4 5 ...
$ M : num 1 2 3 4 5 6 7 8 9 10 ...
I would like to create a new data frame, Z, such that Z <- data.frame(cbind(X, Y)) where:
X <- as.character(unique(df$ID))
> X
[1] "a" "b" "c" "d" "e"
and Y is a vector of the sum of all a's, sum of all b's, sum of all c's, etc...
So, Y should be equal to c(34, 38, 42, 46, 50) and my final result should be:
> Z
X Y
1 a 34
2 b 38
3 c 42
4 d 46
5 e 50
> str(Z)
'data.frame': 5 obs. of 2 variables:
$ X: chr "a" "b" "c" "d" ...
$ Y: num 34 38 42 46 50
To do this, I've tried first turning X into a data frame (is it easier to work with as a data table?):
> Z <- data.frame(X)
> Z
X
1 a
2 b
3 c
4 d
5 e
> str(Z)
'data.frame': 5 obs. of 1 variable:
$ X: Factor w/ 5 levels "a","b","c","d",..: 1 2 3 4 5
and then defining Y as Z$Y <- sum(df[df$ID == Z$X, 2]) but I don't get unique values:
> Z
X Y
1 a 210
2 b 210
3 c 210
4 d 210
5 e 210
I've also tried defining the function f1() like so:
f1 <- function(v, w, x, y, z){sum(v[v$w == x$y, z])}
but that gets me:
> f1(df, 'ID', Z, 'X', 'M')
[1] 0
I have found a function from another post on this forum that does something similar:
f1 <- function(df, cols, match_with, to_x = 50){
df[cols] <- lapply(df[cols], function(i)
ifelse(grepl(to_x, match_with, fixed = TRUE), 'MID',
i))
return(df)
}
This looks for the value "50" in the match_with column and returns the value "MID" to that row of the column designated by cols, provided both columns in the same designated data base df. So, I would need to replace to_x = 50 with something that, instead of looking for the fixed value "50," looks for whatever value is in the column Z$X and, instead of returning the fixed value "MID," returns the sum of the values df[df$ID == Z$X, df$M]. I've attempted these changes myself by writing variations of the following:
f1 <- function(df, cols, match_with, to_x = df[ , 1], x){
df[cols] <- lapply(df[cols], function(i)
ifelse(grepl(to_x, match_with, fixed = TRUE), sum(x),
i))
return(df)
}
but, so far, none of my variations have produced the desired results. This one gave me:
> f1(Z, df, cols = c('Y'), match_with = df$ID, x = df$M)
X Y
1 a 210
2 b 210
3 c 210
4 d 210
5 e 210
Warning messages:
1: In grepl(to_x, match_with, fixed = TRUE) :
argument 'pattern' has length > 1 and only the first element will be used
2: In `[<-.data.frame`(`*tmp*`, cols, value = list(Y = c(210, 210, :
replacement element 1 has 20 rows to replace 5 rows
It seems to be summing the entirety of df$M instead of the subsets where df$ID == Z$X. In other variations it seemed to have problems referencing a column in a second data frame.
I am somewhat new to R and have almost no experience writing user-defined functions (as you probably could tell by this question). Any help would be very much appreciated!

Answer 1

Nevermind ya'll, I think I got it!
> f1 <- function(col1, col2, df2, to_add){
+ lapply(col1, function(i){
+ df2$x <- grepl(i, col2, fixed = TRUE)
+ df3 <- df2[df2$x == TRUE, to_add]
+ sum(df3, na.rm = TRUE)
+ })}
> Z$Y <- f1(Z$X, df$ID, df, c('M'))
> Z
X Y
1 a 34
2 b 38
3 c 42
4 d 46
5 e 50