ddply for sum by group in R

Question

I have a sample dataframe \"data\" as follows:

X            Y  Month   Year    income
2281205 228120  3   2011    1000
2281212 228121  9   2010    1100
22812         


        

Answer 1

I think the package dplyr is faster than plyr::ddply and more elegant.

testData <- read.table(file = "clipboard",header = TRUE)
require(dplyr)
testData %>%
  group_by(Y) %>%
  summarise(total = sum(income),freq = n()) %>%
  filter(freq > 3)

Answer 2

As pointed out in a comment, you can do multiple operations inside the summarize.

This reduces your code to one line of ddply() and one line of subsetting, which is easy enough with the [ operator:

x <- ddply(data, .(Y), summarize, freq=length(Y), tot=sum(income))
x[x$freq > 3, ]

       Y freq  tot
3 228122    4 6778

---

This is also exceptionally easy with the data.table package:

library(data.table)
data.table(data)[, list(freq=length(income), tot=sum(income)), by=Y][freq > 3]
        Y freq  tot
1: 228122    4 6778

In fact, the operation to calculate the length of a vector has its own shortcut in data.table - use the .N shortcut:

data.table(data)[, list(freq=.N, tot=sum(income)), by=Y][freq > 3]
        Y freq  tot
1: 228122    4 6778