R: Producing frequency table by selecting certain rows

Question

I have a minimal example of a data set D that looks something like:

 score person freq
    10      1    3
    10      2    5
    10      3    4
     8      1    3
     7      2    2
     6      4    1

Now, I want to be able to plot frequency of score=10 against person.

However, if I do:

#My bad, turns out the next line only works for matrices anyway:
#D = D[which(D[,1] == 10)]

D = subset(D, score == 10)

then I get:

score person freq
   10      1    3
   10      2    5
   10      3    4

However, this is what I would like to get:

score person freq
   10      1    3
   10      2    5
   10      3    4
   10      4    0

Is there any quick and painless way for me to do this in R?

Answer 1

Here's a base R approach:

subset(as.data.frame(xtabs(freq ~ score + person, df)), score == 10)
#   score person Freq
#4     10      1    3
#8     10      2    5
#12    10      3    4
#16    10      4    0

Answer 2

You can use complete() from the tidyr package to create the missing rows and then you can simply subset:

library(tidyr)
D2 <- complete(D, score, person, fill = list(freq = 0))
D2[D2$score == 10, ]
## Source: local data frame [4 x 3]
## 
##   score person  freq
##   (int)  (int) (dbl)
## 1    10      1     3
## 2    10      2     5
## 3    10      3     4
## 4    10      4     0

complete() takes as the first argument the data frame that it should work with. Then follow the names of the columns that should be completed. The argument fill is a list that gives for each of the remaining columns (which is only freq here) the value they should be filled with.

As suggested by docendo-discimus, this can be further simplified by using also the dplyr package as follows:

library(tidyr)
library(dplyr)
complete(D, score, person, fill = list(freq = 0)) %>% filter(score == 10)