Apply function over data frame rows - r

Question

I'm trying to apply a function over the rows of a data frame and return a value based on the value of each element in a column. I'd prefer to pass the whole dataframe instead of naming each variable as the actual code has many variables - this is a simple example.
I've tried purrr map_dbl and rowwise but can't get either to work. Any suggestions please?
#sample df
df <- data.frame(Y=c("A","B","B","A","B"),
X=c(1,5,8,23,31))
#required result
Res <- data.frame(Y=c("A","B","B","A","B"),
X=c(1,5,8,23,31),
NewVal=c(10,500,800,230,3100)
)
#use mutate and map or rowwise etc
Res <- df %>%
mutate(NewVal=map_dbl(.x=.,.f=FnAdd(.)))
Res <- df %>%
rowwise() %>%
mutate(NewVal=FnAdd(.))
#sample fn
FnAdd <- function(Data){
if(Data$Y=="A"){
X=Data$X*10
}
if(Data$Y=="B"){
X=Data$X*100
}
return(X)
}

Answer 1

If there are multiple values, it is better to have a key/val dataset, join and then do the mulitiplication
keyVal <- data.frame(Y = c("A", "B"), NewVal = c(10, 100))
df %>%
left_join(keyVal) %>%
mutate(NewVal = X*NewVal)
# Y X NewVal
#1 A 1 10
#2 B 5 500
#3 B 8 800
#4 A 23 230
#5 B 31 3100
It is not clear how many unique values are there in the actual dataset 'Y' column. If we have only a few values, then case_when can be used
FnAdd <- function(Data){
Data %>%
mutate(NewVal = case_when(Y == "A" ~ X * 10,
Y == "B" ~ X *100,
TRUE ~ X))
}
FnAdd(df)
# Y X NewVal
#1 A 1 10
#2 B 5 500
#3 B 8 800
#4 A 23 230
#5 B 31 3100

Answer 2

You were originally looking for a solution using dplyr's rowwise() function, so here is that solution. The nice thing about this approach is that you don't need to create a separate function.
Here's the version using if()
df %>%
rowwise() %>%
mutate(NewVal = ifelse(Y == "A", X * 10,
ifelse(Y == "B", X * 100)))
and here's the version using case_when:
df %>%
rowwise() %>%
mutate(NewVal = case_when(Y == "A" ~ X * 10,
Y == "B" ~ X * 100))