Question:
Below works, but is there a better "R way" of achieving similar result? I am essentially trying to create / distribute groups into individual line items according to a user defined function (currently just using a loop).
Example:
df1 <- data.frame(group = c("A", "B", "C"),
volume = c(200L, 45L, 104L)
)
print(df1)
#> group volume
#> 1 A 200
#> 2 B 45
#> 3 C 104
I want the volume to be broken across multiple rows according to group so that the final result is a dataframe where the new volume (vol2 in the below) would add up to original volume above. In this example, I'm applying integer math with a divisor of 52, so my final result should be:
print(df3)
#> group vol2
#> 1 A 52
#> 2 A 52
#> 3 A 52
#> 4 A 44
#> 21 B 45
#> 31 C 52
#> 32 C 52
This works
The code below DOES get me to the desired result shown above:
div <- 52L
df1$intgr <- df1$volume %/% div
df1$remainder <- df1$volume %% div
print(df1)
#> group volume intgr remainder
#> 1 A 200 3 44
#> 2 B 45 0 45
#> 3 C 104 2 0
df2 <- data.frame()
for (r in 1:nrow(df1)){
if(df1[r,"intgr"] > 0){
for (k in 1:as.integer(df1[r,"intgr"])){
df1[r,"vol2"] <- div
df2 <- rbind(df2, df1[r,])
}
}
if(df1[r,"remainder"]>0){
df1[r, "vol2"] <- as.integer(df1[r, "remainder"])
df2 <- rbind(df2, df1[r,])
}
}
print(df2)
#> group volume intgr remainder vol2
#> 1 A 200 3 44 52
#> 2 A 200 3 44 52
#> 3 A 200 3 44 52
#> 4 A 200 3 44 44
#> 21 B 45 0 45 45
#> 31 C 104 2 0 52
#> 32 C 104 2 0 52
df3 <- subset(df2, select = c("group", "vol2"))
print(df3)
#> group vol2
#> 1 A 52
#> 2 A 52
#> 3 A 52
#> 4 A 44
#> 21 B 45
#> 31 C 52
#> 32 C 52
Being still relatively new to R, I'm just curious if someone knows a better way / function / method that gets to the same place. Seems like there might be. I could potentially have a more complex way of breaking up the rows and I was thinking maybe there's a method that applies a UDF to the dataframe to do something like this. I was searching for "expand group/groups" but was finding mostly "expand.grid" which isn't what I'm doing here.
Thank you for any suggestions!
