I want to count the number of occurrences of a factor in a data frame. For example, to count the number of events of a given type in the code below:
library(plyr)
events <- data.frame(type = c('A', 'A', 'B'),
quantity = c(1, 2, 1))
ddply(events, .(type), summarise, quantity = sum(quantity))
The output is the following:
type quantity
1 A 3
2 B 1
However, what if I know that there are three types of events A, B and C, and I also want to see the count for C which is 0? In other words, I want the output to be:
type quantity
1 A 3
2 B 1
3 C 0
How do I do this? It feels like there should be a function defined to do this somewhere.
The following are my two not-so-good ideas about how to go about this.
Idea #1: I know I could do this by using a for loop, but I know that it is widely said that if you are using a for loop in R, then you are doing something wrong, there must be a better way to do it.
Idea #2: Add dummy entries to the original data frame. This solution works but it feels like there should be a more elegant solution.
events <- data.frame(type = c('A', 'A', 'B'),
quantity = c(1, 2, 1))
events <- rbind(events, data.frame(type = 'C', quantity = 0))
ddply(events, .(type), summarise, quantity = sum(quantity))
You get this for free if you define your events variable correctly as a factor with the desired three levels:
R> events <- data.frame(type = factor(c('A', 'A', 'B'), c('A','B','C')),
+ quantity = c(1, 2, 1))
R> events
type quantity
1 A 1
2 A 2
3 B 1
R> table(events$type)
A B C
2 1 0
R>
Simply calling table() on the factor already does the right thing, and ddply() can too
if you tell it not to drop:
R> ddply(events, .(type), summarise, quantity = sum(quantity), .drop=FALSE)
type quantity
1 A 3
2 B 1
3 C 0
R>