dfapply: apply an expression to each row of a data.frame

dfapply

# Chris DuBois
# October 2, 2011

# dfapply: apply an expression to each row of a data.frame

# This can be especially helpful when organizing experimental setups and you want to plot the results from a data.frame.

# s: data.frame, where each row has argument values 
# expr: expression to evaluate on each row of s

# Returns a data.frame with columns created or changed according to expr.
dfapply <- function(s,expr) {
  d <- lapply(1:nrow(s),function(i) {
    e <- evalq(environment(), s[i,], parent.frame())
    eval(expr, e)
    as.data.frame(as.list(e))
  })
  return(do.call(rbind,d))
}

# Example where we want to evaluate fn(a,b) on each row of s.
fn <- function(a,b) a[1]+b[1]
s <- expand.grid(a=1:3,b=1:4)
expr <- expression({
  x <- fn(a,b)
})
y1 <- dfapply(s,expr)

# Alternatively done with sapply.  This approach gets annoying with more complicated examples.
x <- sapply(1:nrow(s),function(i) fn(s$a[i],s$b[i]))
y2 <- cbind(x,s)
stopifnot(all(y1==y2))

# Example where you can return (multiple) vectors for each row of the data.frame
xs <- seq(0,5,by=.01)
s <- expand.grid(a=0:5,b=1:4)
expr <- expression({
  yhat <- a + b*xs
  xs <- xs
})
yhats <- dfapply(s,expr)

head(yhats)
require(ggplot2)
qplot(xs,yhat,data=yhats,colour=factor(b),linetype=factor(a),geom="line")