R: Fastest way to do row wise computation on multiple columns of a data frame

Question

I have a data frame where I want to add another column that's a result of computation involving 3 other columns. The method I am using right now seems to be very slow. Is there any better method to do the same. Here is the approach I am using. ``` library(bitops) GetRes<-function(A, B, C){ tagU <- bitShiftR((A*C), 4) tagV <- bitShiftR(B, 2) x<-tagU %% 2 y<-tagV %% 4 res<-(2*x + y) %% 4 return(res) } df <- data.frame(id=letters[1:3],val0=1:3,val1=4:6,val2=7:9) apply(df, 1, function(x) GetRes(x[2], x[3], x[4])) ``` My data frame is very big and it's taking ages to get this computation done. Can someone suggest me to do it better? Thanks.

Accepted Answer

Everything you're doing is already vectorized which is much faster than any other alternative you'll be offered. You can just call this...

```
with(df, GetRes(val0, val1, val2))
```

or this

```
GetRes(df$val0, df$val1, df$val2)
```

or this

```
GetRes(df[,2], df[,3], df[,4])
```

R: Fastest way to do row wise computation on multiple columns of a data frame

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