Conditionally grouped histograms from my dataset

Question

My current dataset data.dfhas about 420 students who have completed 8 surveys under one of three instructors. escoreis my variable of interest.

    'data.frame':   426 obs. of  10 variables:
     $ ques01: int  1 1 1 1 1 1 0 0 0 1 ...
     $ ques02: int  0 0 1 1 1 1 1 1 1 1 ...
     $ ques03: int  0 0 1 1 0 0 1 1 0 1 ...
     $ ques04: int  1 0 1 1 1 1 1 1 1 1 ...
     $ ques05: int  0 0 0 0 1 0 0 0 0 0 ...
     $ ques06: int  1 0 1 1 0 1 1 1 1 1 ...
     $ ques07: int  0 0 1 1 0 1 1 0 0 1 ...
     $ ques08: int  0 0 1 1 1 0 1 1 0 1 ...
     $ inst  : Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 1 ...
     $ escore: int  3 1 5 5 3 3 4 4 2 5 ...
     

I am wondering how I can generate histograms escorethat are conditionally separated based on the value instfor this observation. In my head, the pseudo code might look like this:

    par(mfrow=c(1,3)) 
    hist(escore, data.df$inst = 1)
    hist(escore, data.df$inst = 2)
    hist(escore, data.df$inst = 3)

but of course this will not work: - (

Ideally, my histograms would look like this:

3 separate histograms of 140 observations, each of which is grouped according to their "inst" Value http://terpconnect.umd.edu/~briandk/escoreHistogramsbyInstructor-1.png

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!

Answer 1

:

library(lattice)
histogram( ~ escore | inst, data=X)

X - data.frame.

Answer 2

ggplot2:

data.df <- data.frame(inst = factor(sample(3, 426, replace=TRUE)), 
                      escore = sample(5, 426, replace=TRUE))
qplot(escore, fill=inst, data=data.df) + facet_wrap(~inst, ncol=3)

alt text http://www.cs.princeton.edu/~jcone/hists.png