Using ddply to apply a function to a group of rows

Question

I use ddply quite a bit but I do not consider myself an expert. I have a data frame (df) with grouping variable "Group" which has values of "A", "B" and "C" and the variable to summarize, "Var" has numeric values. If I use ``` ddply(df, .(Group), summarize, mysum=sum(Var)) ``` then I get the sum of each A, B and C, which is correct. But what I want to do is to sum over each grouping of the Group variables as they are arranged in the data frame. For instance, if the data frame has ``` Group Var A 1.3 A 1.2 A 0.4 B 0.3 B 1.3 C 1.5 C 1.7 C 1.9 A 2.1 A 2.4 B 6.7 ``` The Desired result ``` A 2.9 B 1.6 C 5.1 A 4.5 B 6.7 ``` So, the desired output performs a mathematical function on each grouping of the Group variables, rather than on all instances of the individual Group variables. Can this be done in ddply? Data ``` dat <- structure(list(Group = c("A", "A", "A", "B", "B", "C", "C", "C", "A", "A", "B"), Var = c(1.3, 1.2, 0.4, 0.3, 1.3, 1.5, 1.7, 1.9, 2.1, 2.4, 6.7)), .Names = c("Group", "Va…

Accepted Answer

Here's one way of doing this using the recently implemented `rleid()` function from `data.table` v1.9.6. See #686.

This generates the grouping ids as required:

```
require(data.table) ## v1.9.6+
DT = as.data.table(dat)
rleid(DT$Group)
# [1] 1 1 1 2 2 3 3 3 4 4 5
```

We can use this directly to aggregate as follows:

```
DT[, .(sum=sum(Var)), by=.(Group, rleid(Group))]
#    Group rleid sum
# 1:     A     1 2.9
# 2:     B     2 1.6
# 3:     C     3 5.1
# 4:     A     4 4.5
# 5:     B     5 6.7
```

HTH

Using ddply to apply a function to a group of rows

Solution

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